Public Policy Theses and Dissertations
Permanent URI for this collectionhttp://hdl.handle.net/1903/2803
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Item The Role of the Magnitsky Transnational Advocacy Network in the Selection of Sanctions Targets(2024) Massaro, Arthur Paul; Reuter, Peter; Public Policy; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This research is an exploratory study of foreign policy decision-making regarding Global Magnitsky and other targeted human rights and anti-corruption sanctions. It examines the consequences of a unique provision of the Magnitsky law requiring the government to consider information provided by civil society. This provision led to the generation of a transnational advocacy network dedicated to expanding targets of the Global Magnitsky program and eventually expanding further into advocating for the adoption of Magnitsky-style sanctions in other jurisdictions, as well as providing information for all manner of targeted human rights and anti-corruption sanctions. This research analyzes how this network has been able to influence U.S. foreign policy and the foreign policy of U.S. allies and, more broadly, what this means for transnational relations, sanctions, and civil society. I use qualitative interviews as well as numerous primary sources to trace the process of the evolution of the Magnitsky transnational advocacy network. I demonstrate that there exists such a network, that it is influencing decision-making through its deep integration of civil society and government and the provision of specialized information, and that the conditions for network influence depend on the culture and preferences of enforcing agencies, which I identify.Item The Language of Central Banking: Probing Global Monetary Policy Communications Spillovers and Central Bank Shocks with Natural Language Processing Tools and a Novel Text Database(2024) Baird, Cory; Swagel, Phillip; Public Policy; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The discipline of macroeconomics relies mainly on structured data for empirical research, despite unstructured text data being vastly more abundant. This text data, particularly central bank communications, holds untapped potential for monetary economics research due to their influence on market expectations and policy outcomes like inflation. To help guide monetary policy researchers in exploring the growing universe of text data, this research lays out a foundational framework, both in terms of coding infrastructure and Natural Language Processing (NLP) methods. The first step in building out this infrastructure is through the creation of a new open-source central bank text database consisting of monetary policy communications from 14 countries consisting of 2,418 monetary policy statements. I leverage this novel database to explore the literature on "information effects," which has mainly relied on structured data for empirical analysis despite the possibility that the phenomenon itself is attributable to the linguistic elements or sentiment expressed via central bank communications. Chapter 1 (The Anatomy of a Central Bank Statement and Information Shocks) details the steps necessary to create a reproducible and scalable database of monetary policy statements from a diverse group of countries using the latest open source technologies and modern data science practices. I find that positive co-movement between policy rates and equities (what the literature defines as an "information shock") is a common event, with almost half of all policy rate increases (decreases) occurring alongside higher (lower) equity prices. With linguistic regressions and part-of-speech annotations, I provide novel linguistic evidence that information shocks are likely related to both the future state of the economy \parencite{nakamura2018high} and inflation expectations \parencite{boehm2021beyond}. Chapter 2 (Sentiment Analysis-From Past to Present) develops a novel approach for extracting sentiment at the sentence level using cutting-edge transformers models, the architecture behind many large language models (LLMs). My research demonstrates that transformer models as well as the traditional lexical methods employed in the economic literature, can produce starkly divergent results when applied to the same monetary policy statement. This highlights the critical need to utilize multiple sentiment measures to ensure the robustness of any findings derived from textual analysis. Reinforcing the linguistic evidence from Chapter 1, I show that positive (negative) sentiment is associated with positive (negative) information shocks providing further evidence the shocks are driven by the language of the statement itself. I also show that positive sentiment is associated with higher GDP growth in the quarters following a monetary policy statement. Chapter 3 (Central Bank Shocks and Global Spillovers), aggregates sentiment measures from the previous chapter to produce what I call the Global Policy Stance (GPS). I find that the GPS, led by the U.S., Japan, and Switzerland, tends to co-move with the global financial cycle (Global Asset Prices Factor from \textcite{miranda2020global}). I also find that domestic sentiment, rather than U.S. or global sentiment, is predictive of future policy rate changes suggesting that markets may be more sensitive to the communications of the home country's central bank. This thesis sets a rigorous standard for database transparency and code reproducibility above and beyond what is standard practice in the economics literature today. I will publicly release the codebase encompassing data retrieval, cleaning processes, figure generation, model development, all of which were produced utilizing the open-source Python programming language. Through this public release, I will provide researchers with valuable coding infrastructure that supports the operationalization of best practices in data management, enabling (1) the creation of open-source databases fostering collaboration and automation, as well as (2) the development of reproducible, scalable algorithms for text classification and text cleaning processes. In the future, I intend to further build out the central bank database to include other types of monetary policy communications (e.g., minutes and speeches) while also separately maintaining a repository of text classification algorithms (e.g. positive and negative sentiment) including lexical dictionaries from the literature as well as fine-tuned transformer models.Item AN INTEGRATED ASSESSMENT OF THE FUTURE “HYDROGEN ECONOMY”: DECARBONIZATION POTENTIAL, SOCIETAL IMPLICATIONS, AND POLICY APPROACHES(2024) O'Rourke, Patrick Robert; Hultman, Nathan; Public Policy; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Recently clean hydrogen has captured the attention of policy communities, as evidenced by the publication of hydrogen “roadmaps” or “strategies” by dozens of nations. This is partly because it can be produced from numerous primary energy resources and utilized in a plethora of ways to enable decarbonization. However, there remain open questions as to how the energy carrier should contribute toward carbon dioxide (CO2) mitigation. Additionally, less is known about its impacts on other societal objectives and whether government plans for hydrogen are driven by realistic expectations regarding its ability to facilitate emissions reductions. This dissertation involves three studies which simulate energy transitions within the Global Change Analysis Model (GCAM), each aiming to help illuminate hydrogen’s potential impact on society. First, clean hydrogen supply and demand within the context of decarbonization is investigated. In this research, it is found that hydrogen could be a decentralized energy carrier, as a large portion of its production is enabled by onsite production (i.e., at the location of the end user). In terms of demand, although it will represent a smaller portion of global final energy compared to alternatives, hydrogen enables CO2 mitigation in difficult-to-electrify end uses (e.g., satiating demand for industrial high-temperature heat). The second topic of this dissertation examines hydrogen’s potential implications for the water-energy-food nexus. It is found that clean hydrogen production is unlikely to be a large source of water demand, however, its availability in the forthcoming energy transition could cause larger indirect changes in water demand for many regions of the world. Additionally, clean hydrogen availability is found to enable lower staple crop prices, as it provides a method of reducing CO2 associated with fertilizer manufacturing. Lastly, this dissertation analyzed the Japanese and Korean national hydrogen plans. Aligning with the results from the first research topic of this work, hydrogen’s use within their economies is lower than alternative decarbonization strategies (e.g., direct electrification). As a result, the national plans of both nations are found to be overestimating the scale of hydrogen supply. Further, both countries are generally setting numerical goals for hydrogen deployment in areas of the economy that are less economically efficient compared to alternative sectors where it could both facilitate decarbonization as well as bolster their economies.Item ARE CANADA’S NET-ZERO PLANS ACHIEVABLE, PRUDENT, AND DURABLE?(2024) O'Keefe, Kowan; Sprinkle, Robert; Public Policy; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Canada is a major oil- and gas-producing country that has committed into law the goal of achieving net-zero greenhouse gas (GHG) emissions economy-wide by 2050. Yet the prospect of reduced Canadian oil production has major domestic political and economic implications. Climate change mitigation requires sustained policy engagement, and so policymakers must endeavor to make climate policy that is politically durable. Scenario analysis is a vital decision-support tool for understanding these transition dynamics associated with pursuit of net zero. The first paper in this dissertation explores transition dynamics for Canada across several scenarios with detailed policy representation for achieving net-zero GHG emissions by 2050 using the Global Change Analysis Model (GCAM), an open-source multi-sector dynamics model. The results highlight the importance of effective policy implementation and the variation in transition dynamics attributable to socioeconomic and technological assumptions, carbon dioxide removal scalability, and non-CO2 mitigation. The second paper in this dissertation uses GCAM to examine the sensitivity of Canadian oil production to several external forces in pursuit of net zero. The results show that forces outside of Canada’s control are highly determinative of future oil production levels in Canada. But if Canada moves toward net-zero GHG emissions on its announced timeline, it can reduce the magnitude of the additional declines in Canadian oil production attributable to external forces. Such a move would give Canada greater autonomy to shape transition outcomes in a way that best balances domestic societal priorities. The alternative would be for external forces to thrust a transition upon Canada without regard for such domestic concerns. The third paper in this dissertation examines how these domestic political forces impact Canada’s pursuit of net zero using archival analysis followed by scenario analysis in GCAM. The results of the qualitative policy analysis highlight that a little more than one third (9 of 26) of the modeled policies are less likely to be politically durable, because they fail tests of pan-political acceptability or pan-regional acceptability or both. Reductions in net GHG emissions are significantly smaller in modeled current-policy scenarios where these nine policies are rolled back after 2025. Accordingly, the policies identified as less likely to be politically durable demand greater focus to build stronger cross-party and cross-regional support.Item THE ROLES AND IMPLICATIONS OF AGRICULTURAL AND ENERGY RESOURCES TRADE IN A CLIMATE CHANGE-MITIGATING WORLD(2024) Yarlagadda, Brinda; Hultman, Nathan E.; Public Policy; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Global dependence on agricultural and energy resources trade has grown significantly in the past several decades. In the coming decades, the roles and implications of international trade of various commodities will change, influenced by and important for achieving climate mitigation goals. As globalization increases, new energy technologies emerge, and new climate-oriented trade policies are enacted, there is a need to understand the resulting implications (opportunities and vulnerabilities) on exporters and importers. I present three essays that use the Global Change Analysis Model (GCAM) to evaluate future, inter-regional trade dynamics in a climate-mitigating world. Essay 1 focuses on Latin America and the Caribbean (LAC), a key agricultural exporting region. I show that agricultural market integration (i.e., the reduction of trade barriers) and climate mitigation policies could increase agricultural production and trade opportunities for many LAC economies (particularly in southern South America). Total net export revenue across LAC could reach $110-$270 billion annually by 2050. However, these opportunities could also pose significant economic and environmental trade-offs, including emissions reduction challenges, potential loss of livestock production, increased consumer expenditures, and deforestation and water scarcity pressures. Essay 2 explores the role of liquefied natural gas (LNG) trade as a rapidly emerging technology compared to pipeline natural gas. I analyze how advances in LNG technology, limitations on trade, and climate mitigation policies could affect global and regional vulnerabilities in energy supply. Globally, new additions in LNG and pipeline export infrastructure, range from 330-1330 and 130-440 million tons per annum (MTPA), respectively, by 2050 across scenarios, with the lower end of this range achieved through a transition to a net-zero energy system and limited trade. The results also highlight diverging risks for different gas exporters. For example, Russia, which produces gas largely for pipeline exports, may face larger underutilization due to advances in LNG technology and geopolitical shifts than regions oriented towards domestic and LNG markets, such as the USA and Middle East. Essay 3 evaluates whether import-restrictions on deforestation linked oil crops (i.e., oil palm and soybean) can be effective in reducing deforestation and land use change (LUC) emissions as well as their broader economic implications. I find that current EU restrictions will likely have minimal impact. If extended beyond the EU, import restrictions could drive reductions in cumulative LUC emissions in key oil-crop exporting regions— up to 0.9% in Indonesia, 1.5% in the rest of Southeast Asia, 3.8% in Argentina and 6.7% in Brazil, relative to a scenario with no import restrictions. However, these key exporters could also face losses ranging $4.1-$61 billion in cumulative agricultural production revenue by 2050.Item UNDERSTANDING NONPROFITS’ USE OF DEBT INSTRUMENTS TO FINANCE CAPITAL PROJECTS: PERSPECTIVES FROM THE LANSCAPE OF NONPROFIT BOND FINANCE, NONPROFIT CAPITAL STRUCTURE, AND TAX-EXEMPT BOND CREDIT RATINGS(2024) Sun, Qingqing; Bies, Angela; Public Policy; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This dissertation delves into the significant challenges nonprofit organizations face in accessing tax-exempt bond markets—a vital resource for financing their capital projects and expanding services, particularly in capital-intensive sectors like hospitals and housing-related nonprofits. Although these bonds are intended to provide cost-effective capital for public service entities, nonprofits encounter greater borrowing obstacles than governmental entities, a phenomenon insufficiently studied due to data limitations. To bridge this research gap, my study leverages a unique dataset combining IRS 990 Schedule K forms and municipal bond data, thereby enriching our comprehension of nonprofit financing in the bond market. The overarching question of this research is why nonprofits choose particular debt instruments over others for their capital funding needs and to identify the barricades that hinder more nonprofits from leveraging the municipal bond market efficiently. The first essay examines the nonprofit bond issuance landscape, identifying disparities in interest rates, underwriter fees, and bond rating acquisition among various nonprofit sectors. Notably, charter schools and senior housing nonprofits face higher interest and issuance costs and exhibit lower tendencies to obtain bond ratings, pivotal for signaling creditworthiness and reducing interest rates. Furthermore, there's a uniformly low tendency across all subsectors to obtain credit enhancements, indicating nonprofits' difficulties in persuading credit enhancement agencies willing to take over their default. The reluctance to secure bond ratings and credit enhancements highlights a systemic issue within nonprofit financing, potentially escalating financial risks. The second essay scrutinizes nonprofits' financial decisions concerning mortgages, tax-exempt bonds, and insider loans through the lens of static trade-off (STT) and pecking order theories (POT). Analysis via a Heckman selection model indicates that nonprofits with more diverse revenue streams and with stable source of income have increased usage of mortgages with lower issuance costs and greater repayment flexibility, aligning with STT. Conversely, these nonprofits are less inclined to use tax-exempt bonds, a finding that aligns POT. The results challenge conventional capital structure theories and underscoring the need for novel theoretical perspectives. The third essay explores the impacts of nonprofits' financial conditions on their bond credit ratings. Ordered probit regression with the Heckman selection correction reveal that nonprofits’ tendency towards financial leanness contributes to low bond crediting ratings. Specifically, minimized profits, operating revenue, and cash flows, combined with over-dependence on donations and program revenue lead to weaker credit ratings. This scenario reveals a paradox where financial prudence, intended to foster donor confidence, inadvertently signals limited debt repayment capacity to credit rating agencies, inflating borrowing costs. Collectively, these essays contribute significantly to understanding the financial barriers impeding nonprofits' effective use of tax-exempt bonds, underscoring a high-risk perception regarding nonprofit bonds among investors and financial agencies. The insights garnered from this dissertation also underscore critical areas for future research and policymaking, aimed at facilitating more equitable and efficient capital access for nonprofits, thereby enhancing their ability to serve marginalized communities and fulfill their mission-driven objectives.Item THREE ESSAYS ON DECARBONIZATION STRATEGIES(2024) Luo, Kaifang; Qiu, Yueming; Public Policy; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Efforts toward decarbonization are vital to achieving future net-zero carbon emissions. Managing energy demand, shifting from fossil fuels to low-carbon sources such as renewables, and deploying carbon capture, utilization, and storage (CCUS) technologies are all effective decarbonization strategies. This dissertation comprises three essays exploring demand-side decarbonization strategies.Essay 1 evaluates the effectiveness of the electricity rate structure. This essay examines whether commercial consumers respond to nonlinear pricing schedules. I investigate a four-tiered rate structure from 5/1/2013 to 12/31/2016 in Phoenix Metropolitan, Arizona, including 597 commercial accounts. Hourly electricity consumption data makes it possible to detect consumption changes at each cutoff. This essay finds that consumers with higher usage tend to be more sensitive to average prices, while consumers with lower usage are more sensitive to marginal prices. The results indicate that nonlinear rate structures can reduce electricity consumption, particularly for commercial consumers with lower energy demand. Furthermore, policymakers should tailor conservation policies differently for commercial electricity consumers to manage energy demand. Essay 2 investigates the co-adoption of renewable technologies. While market and behavioral factors have been attributed to the low adoption rate of low-carbon technologies, one factor has yet to be fully explored - the network of renewable energy actors. This essay focuses on the residential co-adoption of solar PV and battery storage. The results confirm the importance of central coordinators and the need for highly cooperative groups among involved RE actors to advocate for co-adoption. Policymakers or policy entrepreneurs may serve as a bridge between isolated actors in the network or facilitate closed-loop relationships between allies, thereby facilitating technological diffusion in the solar and battery sectors. Essay 3 examines the impact of CCUS technologies. A CCUS supply chain captures CO2 and delivers it to a suitable location where CO2 can either be used or injected deep underground for long-term storage. While it reduces carbon emissions, it also poses risks to local communities. This essay examines the net impact of CCUS projects. By combining nationwide CCUS data with property-level transaction data between 1990 and 2021, this essay finds that residents living within 4.2 km of a CCUS facility enjoy an average price premium of 4.14% (or $9,673). Interviews with real estate agents near CCUS projects indicate their positive impact may be attributed to job creation and housing demand. Policymakers can use the information about possible price premiums to influence local perceptions of CCUS technologies and to promote their global deployment.Item EXPLORING THE IMPACT OF EXPENSE DISAGGREGATION AS A FINANCIAL MANAGEMENT TOOL IN PUBLIC INSTITUTIONS OF HIGHER EDUCATION THROUGH A MIXED METHODS APPROACH(2024) Baker, Dylan R; Joyce, Philip; Public Policy; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This mixed methods dissertation investigates the impact that cost-disaggregating tools like the Delaware Cost Study (DCS) have on the expenditure patterns at large, public research universities. It draws on public budgeting and higher education finance literature to form a theory of action that hypothesizes that expense management at such institutions will result in the internal realignment of resources but will not alter the total amount spent. The quantitative model employs a 15-year panel data set comprised of financial and operational activity data for 69 R1 universities to tests the influence of DCS participation against this idea. The primary quantitative outcome shows that total costs are indeed not altered by cost disaggregation efforts, but that spending at universities employing such approaches is, on average, higher for Instruction and Scholarships and lower for Institutional Support and Student Service activities than the spending at non-DCS participants. The results inform the contrasting case selection strategy that highlights three similar constituted universities with differing quantitative results in an extensive interview-based qualitative analysis. The interviews detail the varied positive and negative outcomes of the use of DCS and similar tools, sheds light as to why the quantitative results occurred at each university, and documents the commonalities. Recommendations derived from the combined results of the two research methods signal key tenets that policy makers may utilize to enhance the effectiveness of public financial management for large, complex state-sponsored universities.Item SCHRODINGER’S TECHNOLOGY IS HERE AND NOT: A SOCIO-TECHNICAL EVALUATION OF QUANTUM SENSING IMPLICATIONS FOR NUCLEAR DETERRENCE(2023) Rand, Lindsay Elizabeth; Gallagher, Nancy; Public Policy; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)When and how could technological advances undermine nuclear deterrence? This research uses an interdisciplinary approach to explore the technical, strategic, and social factors that propagate interest in emerging technologies like quantum sensing, and to assess the likely effects on strategic stability. Recent scholarship asserts that new remote sensing technologies may soon provide the capabilities needed to detect, track, and precisely target the delivery systems that constitute a nuclear-armed state’s second-strike capabilities. If true, this would have profound consequences for international security, nuclear force structure planning and arms control. Even if such predictions are not technically feasible, exaggerated expectations generated by strategic or social influences could still negatively impact acquisition and force structure decisions critical to strategic stability and arms control policy. This dissertation proposes an integrated, socio-technical analytical framework to examine the technical, strategic, and social factors that inform U.S. decision-making on new technologies with important military implications. The framework improves upon existing research in security studies literature by integrating technical projection methods and science and technology studies theories. Before applying the framework to the contemporary case of quantum sensing, the framework’s operability is demonstrated through five historical case studies: ballistic missile defense, hypersonics, satellite imagery, remote vision, and isomer weapons. These case studies illustrate the intricate interplay among technical, strategic, and social factors that has shaped prior U.S. decisions about pursuing technological innovations related to nuclear deterrence, often leading to over-investment as a strategy to hedge against technological surprise. The quantum sensing case study begins with a technical assessment to determine the realistic advances that can be expected, and the likelihood of disruption to a core feature of stable nuclear deterrence: confidence in the survivability of retaliatory forces. It surveys experimental results to identify sensitivities of current quantum sensor prototypes and theoretical literature to evaluate the likelihood of performance gains as R&D progresses. It then estimates how much these projected capabilities could improve submarine detection and missile accuracy applications in the next 10 years. It finds that quantum sensing will afford more evolutionary, rather than revolutionary, improvements in comparison to existing capabilities. The dissertation then surveys the types of strategic narratives and social dynamics that had important effects on prior decisions about efforts to innovate other strategically relevant technologies, highlighting how they also appear to be shaping debates and decisions about quantum sensing. By assessing competing claims about quantum sensing’s impact on second-strike vulnerability, this dissertation explores how diverging deterrence theories amplify disagreements over the impact of new technologies. It also evaluates the social factors that propagate expectations for quantum sensing across the respective social worlds of technologists and capability seekers, finding that realistic assessments are further frustrated by divides between technical and non-technical literatures and classified information barriers. Based on these findings, policymakers should anticipate continued pressure to pursue emerging technologies like quantum sensing, regardless of patent technical limitations, due to a combination of social dynamics and strategic narratives that support damage limitation deterrence postures. While a technology hedging strategy may seem like an innocuous way for policymakers to appease stakeholders with diverging viewpoints on the risks and benefits of emerging technologies, this dissertation suggests that hedging is likely to galvanize social, strategic, and technical momentum that ultimately signals innovation, fosters competition, and manifests strategic effects, regardless of the initial policy intent.Item Essays on Natural Disasters and Fiscal Resilience(2023) Prabowo, Aichiro Suryo; Joyce, Philip G.; Public Policy; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This dissertation attempts to bridge two fields within public policy, sustainability and public budgeting and finance. Natural disasters have become more frequent, intense, and costly over the last few decades, and this study contributes to the discourse through a public finance lens. I develop three separate but interrelated essays, which seek to understand how environmental shocks like natural disasters affect government budgets, and what actions governments should take to maintain fiscal resilience and sustainability. The first chapter evaluates the impact of flooding events on state government fiscal conditions. I construct a dataset with panel data from 50 U.S. states between 1997 to 2020 and employ a two-way fixed-effects model. The results show that increased severity of flooding leads to higher intergovernmental revenue two years after the disaster, but states do not necessarily pass down more funds to localities. There is also evidence that an increased flooding severity coincides with increased state tax revenue during and one year after the disaster. While federal assistance can help states stabilize during and after an emergency, I argue that it may also create problematic incentives. Specifically, federal transfers may discourage states from allocating sufficient funds for ex-ante flood mitigation. The second chapter examines whether and how government attention to hurricanes developed over time. I analyze budget documents from 2005 to 2020 across seven hurricane-prone states in the U.S.: Alabama, Florida, Georgia, Louisiana, North Carolina, South Carolina, and Texas. While prior studies focus on budget data, my study is the first to exploit the narrative portions of the budget documents using textual analysis. Computational text analysis is used to identify and quantify government attention toward different policy areas, including disaster management in connection with hurricanes. Cases from Louisiana, Alabama, and Florida show that an increased incidence of major hurricanes coincides with higher attention to hurricanes in the budget documents. There is also evidence that the attention to hurricanes is associated more with reactive rather than proactive measures, calling into question the general preparedness of most state governments for future disasters. The third chapter surveys the government’s disclosure of risks associated with natural disasters. It is intended as an exploratory analysis using audited financial reports from 50 U.S. states between 2002 and 2016. Audited financial reports are more technical and less political than the budget documents examined in my second chapter. I combine qualitative analysis with computational text analysis to understand the narrative portions of the source document. The results show that state governments do not widely disclose information regarding disaster risk despite the increasing threat of natural disasters. States that disclosed disaster risk in the past tend to disclose the same information in the future and past years, suggesting significant inertia in financial reporting. Finally, based on selected cases in hurricane-prone states, the study finds proactive as well as reactive risk disclosure, suggesting the need for governmental accounting standards to incorporate mechanisms that specify how disaster risk should be recognized, measured, and presented in the financial reports.