UMD Theses and Dissertations
Permanent URI for this collectionhttp://hdl.handle.net/1903/3
New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a given thesis/dissertation in DRUM.
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Item Foreign Direct Investment in Authoritarian States(2023) Englund, Chase Coleman; Allee, Todd; Government and Politics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)In this dissertation, I examine autocracies and demonstrate why some autocratic regimes attract considerable investment whereas others do not. I advance two primary claims. The first is that autocratic regimes in which there is political competition actually receive less FDI than those in which there is less competition. Autocratic states tend to have weak institutional protections for investors, which causes greater uncertainty for businesses that fear costly policy changes. Therefore, when political competition in autocracies is greater, investors become more cautious and FDI inflows decline. The second claim is that FDI is more targeted to certain sectors in autocratic states with less political competition. This is because autocratic leaders seek to use FDI as a private good to favor members of their winning coalition. Therefore, autocrats with smaller coalitions (i.e., less political competition) will use policy to steer the benefits of FDI more narrowly. This is important because the use of FDI as a private good in this way tends to entrench authoritarianism. In analyzing both claims, I also examine the relative number of economic elites in a state, which I argue is an important and fundamental indicator of competition over policy (alongside the political measures), because it determines the size of an autocrat’s winning coalition. I find strong support for both of these hypotheses, using a wide range of novel data that I have compiled from several unique sources and various private organizations. I examine the volume and sectoral concentration of FDI in thousands of cases involving more than 100 non-democratic states over a 42-year period, beginning in 1980. In order to measure foreign investors’ perceptions of the policy environment in nondemocratic states, I also utilize data from an automated textual analysis of quarterly earnings calls of publicly traded firms located in authoritarian settings. Even after controlling for other factors, I first find that greater political competition is associated with greater perception of risk by foreign investors and lower FDI inflows. To measure the number of economic elites relative to economic activity, I employ a novel measure of stock market concentration that estimates the degree to which a market is either oligarchic or diversified. These results are important and timely because many of the largest recipients of FDI globally are now autocratic states. This means that large segments of the global population will depend on authoritarian governance to attract FDI, which is widely considered important to global economic development. Furthermore, understanding whether or not we can expect FDI to have a democratizing impact on autocratic government is crucial to developing expectations about how FDI will shape global politics in the decades to come.Item On Engineering Risks Modeling in the Context of Quantum Probability(2020) Lee, Yat-Ning Paul; Baecher, Gregory B; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Conventional risk analysis and assessment tools rely on the use of probability to represent and quantify uncertainties. Modeling complex engineering problems with pure probabilistic approach can encounter challenges, particularly in cases where contextual knowledge and information are needed to define probability distributions or models. For the study and assessment of risks associated with complex engineering systems, researchers have been exploring augmentation of pure probabilistic techniques with alternative, non-fully, or imprecise probabilistic techniques to represent uncertainties. This exploratory research applies an alternative probability theory, quantum probability and the associated tools of quantum mechanics, to investigate their usefulness as a risk analysis and assessment tool for engineering problems. In particular, we investigate the application of the quantum framework to study complex engineering systems where the tracking of states and contextual knowledge can be a challenge. This study attempts to gain insights into the treatment of uncertainty, to explore the theoretical implication of an integrated framework for the treatment of aleatory and epistemic uncertainties, and to evaluate the use of quantum probability to improve the fidelity and robustness of risk system models and risk analysis techniques.Item RELATING RISKS TO PAY FACTORS FOR HIGHWAY PAVEMENTS THROUGH MONTE CARLO SIMULATION(2019) Zhao, Yunpeng; Goulias, Dimitrios G; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The majority of State Highway Agencies (SHAs) now employ statistical-based specifications for the acceptance of highway materials and pavement construction. The parameters of these statistical acceptance plans are specified based on engineering judgment and may result in a high level of risk to both agency and contractor. In order to appropriately apply such specifications to the pavement construction industry, the associated production quality (i.e., materials and construction variability) needs to be well understood by all parties involved and its potential impacts require to be assessed. To address this objective of this study was to: (i) quantify the risks to the agencies and contractors (i.e., Type I and Type II errors); (ii) examine how the key components in a statistical acceptance plan impact its performance; and, (iii) identify a methodology to balance the risks and pay factors. Risk and pay factor analysis were conducted for both single and multiple quality characteristics through Monte Carlo simulation, and the development of Operating Characteristic, OC, curves. Furthermore, case studies were presented to demonstrate the value of the analyses proposed in this study. The methodology and findings identified in the study can be applied elsewhere to evaluate the acceptance plans and the associated risks pertinent to pavement construction and the production of highway materials.Item The Politics of Disaster: The Philosophical Production of Risk and Responsibility(2017) Newton, Summer Dawn; Butterworth, Charles; Government and Politics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Failed government responses to severe disasters, including Hurricane Katrina, have led to political repercussions for public institutions tasked with preventing, mitigating, and recovering from disasters. This dissertation investigates the emergence of the public expectation that governments have an obligation to manage their disordered effects. I look to early modern philosophers Hobbes and Machiavelli to explicate the philosophical production of risk and responsibility inherent in this political interpretation of disaster. A careful reading of Machiavelli and Hobbes articulates the reconfiguration of humanity’s relationship with nature, the state, and misfortune. Individuals were no longer to live in accordance with a harmonious nature, but transform it to better suit bodily interests. Machiavelli describes this capacity for transformation as virtue while Hobbes points to human artifice. Machiavellian virtue tamed variable fortune while Hobbesian artifice imposed predictability on disordered nature through the institution of the Leviathan. The resulting social contract arrangements of political authority established citizens’ duty of obedience and the sovereign’s responsibility for the welfare of its citizens, including during periods of disaster. Philosophy transitioned from the cultivation of the soul among the few to the universal provision of self-preservation. These philosophical developments coincided with shifts in explanatory models communities used to attribute causality in disasters. I present four models that assign causality to divine will, random chance or accident, nature, and human agency. In the twenty-first century, the human agency model predominates as human intervention into nature poses challenges in disentangling human activity from natural processes. Earlier historical periods deployed different explanatory models that necessitated non-political remedies, obligation, and blame. The 1755 Lisbon earthquake serves as a waypoint between the early modern and contemporary interpretations of disaster where authorities, victims, and observers debated its cause. In disaster research, human agency is examined in vulnerability analysis which views disasters as the intersection between hazards and ongoing political, economic, and social processes that produce patterns of vulnerability such as those apparent in the “man-made” catastrophe Hurricane Katrina. The very technologies and development strategies intended to increase predictability and control over nature increase the disordered effects inherent in disasters.Item RISK-BASED MULTIOBJECTIVE PATH PLANNING AND DESIGN OPTIMIZATION FOR UNMANNED AERIAL VEHICLES(2016) Rudnick-Cohen, Eliot Sylvan; Herrmann, Jeffrey W; Azarm, Shapour; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Safe operation of unmanned aerial vehicles (UAVs) over populated areas requires reducing the risk posed by a UAV if it crashed during its operation. We considered several types of UAV risk-based path planning problems and developed techniques for estimating the risk to third parties on the ground. The path planning problem requires making trade-offs between risk and flight time. Four optimization approaches for solving the problem were tested; a network-based approach that used a greedy algorithm to improve the original solution generated the best solutions with the least computational effort. Additionally, an approach for solving a combined design and path planning problems was developed and tested. This approach was extended to solve robust risk-based path planning problem in which uncertainty about wind conditions would affect the risk posed by a UAV.Item Electricity Markets Price Risk, Pollution, and Policies(2015) Werner, Daniel Patrick; Houde, Sebastien; Agricultural and Resource Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The electricity sector is a significant contributor to the economic and environmental health of the United States, with annual revenues well over \$300 billion and responsibility for approximately one third of all carbon emissions. The last several decades have brought significant changes to economic and environmental policies applicable to the electricity sector, including market restructuring and a variety of air quality improvement policies. This thesis builds on previous research of these issues through three related essays on energy economics and policy. The first essay examines the local environmental impacts that can be attributed to renewable portfolio standards. Renewable portfolio standards (RPS) have been adopted by the majority of states in the U.S. to encourage electricity from renewable sources. Previous studies omit an analysis of local and regional pollutants, so this paper provides an empirical investigation into pollutant reductions from RPS while accounting for policy heterogeneity across states. Using a nation-wide panel of pollution monitoring stations in conjunction with local and national economic data, I find that adopting RPS results in significant sulfur dioxide reductions and modest nitrogen oxide reductions. I find no evidence of particulate matter reductions. Lastly, the analysis shows that pollution reductions are driven by groups of states whose neighbors also adopt RPS, which is likely because of pollution spillover effects. The second essay examines the importance of ramping cost to electricity price volatility. High price volatility has plagued electricity market participants for decades and is increasingly important in the context of growing intermittent renewables. Although electricity market price behavior generally has been well studied in the last decade, the literature is sparse when discussing the importance of generator ramping costs to price volatility. This paper contributes to the literature by first formalizing the intuitive link between ramping costs and price volatility in a multi-period competitive equilibrium. The fundamental result of the model shows how price volatility rises with ramping costs. This notion is tested empirically using a pooled event study regression, a two-stage least squares (2SLS) specification, and a generalized autoregressive conditional heteroskedasticity (GARCH) model. The econometric results all confirm that price volatility is significantly decreased by additional natural gas capacity, which has comparatively low ramping costs. This marks the first rigorous study to quantify the pecuniary externalities within the New England market's generating profile. A simulation also explores how annualized volatility changes over time during a shifting generation profile, noting that natural gas generators can offset the volatility increases from increasing wind generation. Lastly, there is no evidence that natural gas capacity additions reduce the forward premium. The third essay examines price convergence in the wholesale electricity markets in the context of transaction costs on virtual bids. Virtual bidding has been introduced in most restructured electricity markets in the United States with the intent to manage price risk, increase financial liquidity, and minimize deviations between forward prices and spot prices. Previous literature argues that even without virtual bids, generators can attempt to exploit the forward premium through altering bids related to physical scheduling, which is a costly way to induce price convergence. While previous literature has shown that the introduction of virtual bids does lead towards price convergence, it is also a relatively large market shock that potentially introduces new market participants with different risk preferences. This paper is the first to explicitly test the effect of increasing virtual bid transaction costs on forward price premiums using a natural experiment in a market where virtual bidding is already established. Using high-frequency price data with an event study approach, I find that increasing transaction costs on virtual bids leads to significant increases in forward premiums and significant decreases in the total number of cleared virtual bids. Additionally, my analysis supports recent literature arguing that the day-ahead prices have converged to become an unbiased predictor of real-time prices, which is an important condition for efficient markets. Lastly, I find no evidence that increasing transaction costs on virtual bids translates to increases in intra-day price volatility.Item A Systems Reliability Approach to Flow Control in Dam Safety Risk Analysis(2014) Komey, Adiel; Baecher, Gregory; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Most contemporary risk assessment techniques, such as failure modes and effect analysis (FMEA), fault tree analysis (FTA), and probabilistic risk analysis (PRA) rely on a chain-of-event paradigm of accident causation. Event-based techniques have some limitations for the study of modern engineering systems; specifically hydropower dams. They are not suited to handle complex computer-intensive systems, complex human-machine interactions, and systems-of-systems with distributed decision-making that cut across both physical and organizational boundaries. The emerging paradigm today, however, is not to analyze dam systems separately by breaking the major disciplines into stand-alone vertical analyses; but to explore the possibilities inherent in taking a systems approach to modeling the reliability of flow-control functions within the entire system. This dissertation reports on the development and application of systems reliability models to operational aspects of a hydropower cascade in Northern Ontario: The Lower Mattagami River (LMR) Project operated by Ontario Power Generation (OPG). The reliable performance of a spillway system depends on the many environmental and operational demand functions placed upon it by basin hydrology, the hydraulic conditions at reservoirs and dams, operating rules for the cascade of reservoirs in the basin, and the vagaries of human and natural factors such as operator interventions or natural disturbances such as ice and floating debris (Regan, 2010). These systems interact to control floods, condition flows, and filter high frequencies in the river discharge. Their function is to retain water volumes and to pass flows in a controlled way. The reliability of flow-control systems is a broad topic that covers structural, mechanical, electrical, control systems and subsystems reliability, as well as human interactions, organization issues, policies and procedures. All 3 of these occur in a broad spectrum of environmental conditions. A systems simulation approach is presented for grappling with these varied influences on flow-control systems in hydropower installations. The Mattagami River cascade operated by Ontario Power Generation is a series of four power stations along the Mattagami River and the Adams Creek bypass channel from Little Long GS at the top to the cascade to the Mattagami River below Kipling GS at the bottom. The number of riparians in the river flood plain is few and there is no commercial riverine navigation, so potential loss of life is small or negligible and operational safety dominates. Upstream of Little Long dam is a seasonally-varying inflow and a reservoir. The remaining three dams downstream (Smokey Falls, Harmon, and Kipling) have little storage capacity. Each dam has two vertical lift gates and all four structures have approximately the same spillway capacity. Far downstream, the river discharges into Hudson's Bay. Hydrological and climate frequency data are available for a period of 50 years. The problem facing the project was to conceptualize a systems engineering model for the operation of the dams, spillways, and other components; then to employ the model through stochastic simulation to investigate protocols for the safe operation of the spillway and flow control system. Details of the modeling, analysis, and results for safe operation of the cascade are presented.Item Fire Hazard of the Contemporary American Home(2014) Hanson, Robert E.; Milke, James A; Fire Protection Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Annual direct property damage for one- and two- family residential fires is estimated as $5.9 billion in the United States. Recent research has suggested that the level of fire hazard in contemporary homes is greater than legacy homes. This study utilizes national fire incident data from 2003 to 2010 to examine trends and characteristics of residential fires. The Item First Ignited and Heat Source for fires are analyzed in a risk model. Structural Member is the Item First Ignited that contributes the greatest amount of risk in one- and two- family houses. The Heat Source for Structural Member is concentrated among three main categories: Operating Equipment, Electrical Arcing, and Hot or Smoldering Objects. Grouping together the items Upholstered Sofas, Mattresses, and Bedding as representing soft furnishings in the house, contribute the second greatest amount of risk. The main Heat Source for these items is Other Open Flame or Smoking MaterialsItem Assessing the Cost of Risk for New Technology and Process Insertion(2013) Lillie, Edwin Thomas; Sandborn, Peter; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Adoption and insertion of new technologies and processes into systems is inherently risky. A cost model that forecasts the cost of risk associated with inserting new technology into a system has been developed. The model projects the cost of inserting new processes, projects the impact of the processes on the cost of risk for the system, and performs a cost-benefit analysis on the adoption of proposed new processes. The projected cost of failure consequences (PCFC) is defined as the cost of all failure events (of varying severity) that are expected to occur over the service life of the system. The PCFC is uncertain, and the potential positive impact of adopting new technologies into the system is to reduce the cost of risk and/or reduce its uncertainty. A case study that assesses the adoption of a lead-free solder control plan into systems that previously used tin-lead solder has been performed.Item AN EXTENSION OF THE RISK PERCEPTION ATTITUDE (RPA) FRAMEWORK: EXAMINING THE RELATIONSHIPS BETWEEN THINKING STYLE, LOCUS OF CONTROL, ANXIETY, AND INFORMATION SEEKING(2013) Patel, Sejal; Wolvin, Andrew; Turner, Monique M; Communication; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The purpose of this dissertation was to reexamine the effects of psychological determinants, specifically risk perceptions and self-efficacy beliefs as predicted by the Risk Perception Attitude Framework (RPA) (Rimal & Real, 2003) on anxiety, information seeking behavior, and knowledge acquisition. Additional goals of this dissertation were to test anxiety as a mediating variable between RPA group membership and information seeking, as well as between RPA group membership and knowledge acquisition; to begin to understand what types of information each of the RPA groups seek; and to test the RPA framework as a model. Furthermore, this dissertation extended the RPA framework by incorporating the effects of cognitive processing, namely thinking style (Nisbett, Peng, Choi, & Norenzayan, 2001) and locus of control (Rotter, 1954) on anxiety to increase the predictive power of the RPA framework model. After conducting a pilot test, it was determined that the context of the experimental messages would be about human papillomavirus (HPV). The data supported the hypotheses that those in the anxious group (individuals with high risk perceptions and low self efficacy beliefs) experienced higher levels of anxiety than the other groups, that the RPA framework was a viable model for predicting information seeking and knowledge acquisition, and finally, that cognitive processing (i.e. thinking style and locus of control) increased the predictive power of the RPA framework. However, the data indicated that that the relationship between RPA group membership (based on an interaction between perceived risk and self efficacy beliefs) and HPV information seeking, as well as knowledge acquisition was not mediated by anxiety. Participants who engaged in HPV information seeking were predominantly interested in finding out general information regarding the virus, rather than specific to risk or efficacy information. Limitations, implications, practical application and future directions are discussed.