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Essays on Multinational Behavior
Get PDFThis dissertation studies issues regarding the tax avoidance behavior of multinational corporations. It is composed of three chapters. The first examines the differential impact of the Tax Cuts and Jobs Act of 2017 on firm profit-shifting behavior. The second constructs a theoretical model in which the introduction of tax havens to a standard trade model leads to an oversupply of multinational exports and a decrease in public welfare. The third sheds light on multinational responses to the Great Recession of 2008. The US corporate income tax rate used to be the highest in the developed world, yet multinationals were able to lower their tax burden via the strategic transfer pricing of intra-firm trade. The Tax Cuts and Jobs Act of 2017 (“TCJA”) changed corporate profit-shifting incentives by reducing the US corporate income tax rates as well as by moving from a worldwide to a territory taxation regime. Using Census micro-data, I examine how these provisions of the TCJA differentially affected corporate profit shifting between countries with consistently lower corporate income tax rates and those which post-TCJA now had higher tax rates than the US. I find that in the years after the TCJA came into effect, profit shifting to countries with now-higher corporate tax rates fell by between 10.4 to 12.8 percentage points relative to countries whose tax rates remained lower; however, profit-shifting to those countries increased between 8.8 to 11.6 percentage points relative to the pre-period. Under what circumstances does tax avoidance behavior cause a rise in exports? I build a three-country Melitz-type model consisting of two non-haven countries and one tax haven. Goods are traded between the non-havens, while taxes can be shifted to the haven. With low elasticities of substitution, firms that would remain non-exporters are incentivized to become multinationals in order to shift their domestic profits to the tax haven. While the model is not formally closed, I show that the introduction of tax havens can lead to reductions in public good provision, increases in prices, and a decrease in welfare. The Great Recession was characterized by the reversal of many long-standing trends. Unemployment rose, trade fell, and larger, more productive firms cut jobs and took losses more than smaller ones. Simultaneous to these phenomena, I find a reversal of the regular pattern with respect to profit shifting behavior. Under normal circumstances, firms use internal transactions to reallocate profits to lower-tax jurisdictions. During the Great Recession, however, I find a reversal of this pattern, with lower tax jurisdictions now moving money into the United States. Prior to the Great Recession, firms exporting to a country with a 10 percent lower corporate income tax difference than the United States would underprice their exports by approximately 4.4 percentage points; during the Great Recession, we would expect an overpricing of that same good by approximately 13.3 percentage points
EXPLORING THE INTERPLAY OF RESTORATIVE JUSTICE, MENTAL HEALTH, AND SUPPORT STRUCTURES IN SHAPING STUDENT OUTCOMES
No full textIn recent years, educational policymakers and researchers have increasingly recognized the complex interplay between school discipline, mental health, and the availability of support personnel, and their cumulative impact on student outcomes. My dissertation aims to investigate these interrelated factors through the lens of three distinct but complementary studies. Each study examines different aspects of this multifaceted issue: the effectiveness of Restorative Justice (RJ) reforms in school discipline, the influence of access to mental health resources on student disability diagnosis, and the long-term economic impact of mental health issues on young adults. The first study of my dissertation, titled Moving Away from ‘Zero-Tolerance’ Policies: Evidence from Restorative Justice (RJ) Reforms in Texas and Michigan Schools , assesses the causal impact of RJ as an alternative to exclusionary discipline. RJ aims to foster positive student behavior by focusing on repairing harm and building relationships, as opposed to punitive measures like suspension and expulsion. I use a novel penalized synthetic control method to compare the effects of RJ in school districts in Texas, and then in Michigan, revealing critical insights into how implementation fidelity and local context influence RJ’s effectiveness. This research has significant implications for policymakers, offering evidence on how RJ can reduce suspensions, improve school climate, and address the root causes of behavioral issues in a more equitable manner. The second component of my dissertation examines the relationship between mental health resources and the diagnoses of students with disabilities (SWDs). Drawing on student-level data from the North Carolina Education Research Data Center (NCERDC), I analyze how the distance to mental health services affects diagnoses and distribution of disability categories in students with varying disabilities. This research is particularly timely, as it speaks to the growing concerns about the systemic challenges faced by SWDs. My third project explores the long-term economic impacts of mental health issues among high school students. While the mental health crisis among U.S. youth is widely acknowledged, there is limited research on how mental health challenges in adolescence affect future economic outcomes. This study bridges an important gap in the literature by connecting student mental health in young adulthood with later life labor market outcomes, such as educational attainment. By doing so, I aim to inform both education and mental health policy to promote earlier and more targeted interventions for at-risk students. The findings could be transformative in reshaping how schools, communities, and policymakers address mental health as a key component of students’ educational experiences. This dissertation offers a multifaceted perspective on improving educational practices and policies. The insights gained from this research have the potential to guide future interventions and support mechanisms, ultimately leading to more effective and equitable educational environments for all students
DISPARATE PATTERNS IN U.S. EMERGENCY MEDICAL SERVICES AND DATA MISSINGNESS AS A SOCIO-TECHNICAL DETERMINANT OF HEALTH
Get PDFUnderstanding health disparities is fundamental to population health and is essential for design and promotion of health policies that protect individuals from inequitable access, unfair treatment, and discrimination. However, despite broad reliance on technology and digital data, missingness is a common issue in patient health records. This research aspired to increase understanding of health outcome divergence through the lens of emergency medical events in the United States. Retrospective study focused on outcome missingness in the National Emergency Medical Services Information System (NEMSIS) years 2017 through 2023, a voluminous public research dataset consisting of roughly a quarter billion patient events. Only a small fraction (\u3c1%) of NEMSIS records include a definitive end-of-event status i.e., the patient “lived” or “died.” As a result, while the U.S. 9-1-1 emergency medical response systems are comprehensive, gauging success of their principle function, safely delivering a live individual, who is experiencing a life-threatening medical event, to a hospital emergency department, is challenging. A consequence of outcome missingness is that when differences occur in health care for any reason – including social factors, local resource inequities, discrimination, etc. – impact on patient survival is untestable. U.S. history of EMS and its evolution to prehospital health care are important because more and more people use 9-1-1 services in lieu of access to primary care and for medical emergencies caused by untreated conditions. This equal access is protected by the Emergency Medical Treatment and Labor Act (“EMTALA”), which prevents hospitals and EMS agencies receiving Medicare funds from refusing to treat patients. For now, EMS is a social equalizer by its natural control of access. However, recent studies have shown localized EMS disparities by race/ethnic, sex, social, and geographic location. This dissertation research offers the following contributions. (i) Accurately imputed individual patient “dead” or “alive” outcomes are imputed for \u3e150 million EMS patient events (2017 to 2023). Machine learning methodology trained, tested, and cross-validated a multi-layer neural network model that improved “dead” category accuracy (sensitivity; recall) by 35 percentage points over a previously published method. The model achieved almost 90% balanced accuracy for both “dead” and “alive” predictions despite severe category imbalance, and without evidence of over-fitting. Stratified K-fold cross validation was performed to minimize general bias and to provide sensitivity analysis best-practice to address missingness. (ii) First-of-a-kind national EMS mortality benchmarks are estimated for out-of-hospital cardiac arrest (OHCA), opioid overdose, respiratory arrest, sepsis, ST-segment elevation myocardial infarction (STEMI), stroke, trauma, and unresponsive patient. The benchmarks provide reference points for future research to evaluate interventions and sub-population outcome disparities. (iii) Several disparate mortality patterns are revealed by medical emergency category, sex, race/ethnicity, age group, and geographic location. (iv) Models and systems for responsible AI-based population health are advanced by rigorously demonstrating that machine learning accurately predicts missing EMS patient outcomes. (v) New methodology is demonstrated for analyzing and visualizing threshold selection and specificity / sensitivity trade-off in binary classification, and for estimating population-level mortality rates by leveraging fractional response regression. (vi) Results from a previously published study are reproduced and replicated to anchor the work by comparison to the previous authors’ hand-crafted imputed outcomes. (vii) Finally, this work contributes to the understanding of population health and the notion of missing data as a socio-technical determinant of health
Maximal Simple Regular Matroids
No full textIn 1980, Seymour completely classified regular matroids. In this thesis, we use this classification to provide a complete list of maximal simple regular matroids up through rank six. In each rank, exactly one of these is graphic. Additionally, there are one, two, and eight cographic, but not graphic, maximal simple regular matroids in ranks four, five, and six, respectively. In rank five, we also have the 10-element sporadic matroid, and in rank six we have a 12-element maximal simple regular matroid and 16-element maximal simple regular matroid, both of which are decomposable matroids that are not graphic, cographic, or sporadic. In particular, rank six is the first rank we see decomposable matroids that are not also graphic or cographic. In addition, rank six has a maximal simple cographic matroid that is not maximal simple regular
Identifying Strategies in Moral Decision Making
Get PDFThis study explored the strategies used in moral decision-making, within the context of selfdriving car scenarios. Our goal was to uncover the strategies people use when faced with moral dilemmas, using methodological approaches previously applied to the study of decision-making. The strategies that we were interested in were those that align with the ethical frameworks of utilitarianism, deontology or a blend of the two. In this study, participants were confronted with a series of moral dilemmas involving self-driving cars. Their choices and decision-making processes were analyzed using Machine Learning Strategy Identification (MLSI), which incorporated features related to the information participants attend to on the screen, as measured through eye tracking. This approach not only broadened the application of MLSI to moral decision-making but also expanded it to include eye-tracking data, whereas it previously incorporated only mouse-tracking data, final choice outcomes, and reaction times
Express Yourself! Biculturalism, Ethnic Identity & Expression Through Instagram
Get PDFThis qualitative study examines the relationship between biculturalism, ethnic identity, and Instagram use among second-generation Pakistani-Americans. To answer the research questions for this cross-sectional study, the method of virtual, semi structured in-depth interviews was utilized to collect data. Through interviews with second-generation Pakistani-Americans, the researcher explored how Instagram use intersects with ethnic identity and bicultural experiences. Interview data was collected, transcribed, analyzed, and categorized into various themes. Results suggest that Instagram plays a significant role in shaping and expressing ethnic identity, providing a platform for connection, cultural exchange, and personal exploration. This study contributes to understanding the role of social media in identity formation among second-generation Pakistani-Americans, addressing a gap in the literature on ethnic identity and digital self-expression, and offering insights that may apply to other immigrant communities. Keywords: Qualitative Interviews, Ethnic Identity, Instagram, Pakista
EXPLORING THE THERAPEUTIC POTENTIAL OF ART MATERIALS THROUGH DIRECT ENGAGEMENT IN THE ART PROCESS: A HEURISTIC ART-BASED RESEARCH STUDY
Get PDFThis study explored the therapeutic potential of various art materials to enhance future client sessions. Utilizing a heuristic art-based approach, I explored seven materials, including: acrylic paint, watercolor, paper, colored pencils, air-dry clay, charcoal, and oil pastels; each approached in five distinct ways. The materials were selected for their affordability, accessibility, and versatility in creative expression. After each session, I completed a self-designed four-question questionnaire to reflect on my emotional and physical interactions with the materials. I then wrote a thick description of each material, drawing from my personal experience and evaluating how it could be used with clients in future art therapy sessions. I identified themes, which now inform how I plan to incorporate each material in my work as an art therapist
WHAT MAKES ME FEEL COLD IS NOT WINTER OR NIGHT
Get PDFThis thesis examines how cinematic form can render visible the lived experiences of displacement, temporal disjunction, and marginalization among transnational subjects, particularly international students navigating between legal regimes, emotional landscapes, and cultural systems. Through a practice-led methodology anchored in film theory, phenomenology, and spatial analysis, the project explores how space and time function not as narrative backdrops but as agents of affective rupture. The film WHAT MAKES ME FEEL COLD IS NOT WINTER OR NIGHT employs disjunctive spaces—such as parking garages, mini-golf courses, and restaurant interiors—as sites of perceptual tension, drawing from Deleuze’s concept of the “any-space-whatever.” These locations, stripped of dramatic action, expose the affective folds and atmospheric pressures that shape diasporic life. Temporally, the film resists linearity, adopting extended long takes, visual stillness, and asynchronous soundscapes to evoke the “liquid time” of transnational existence—a temporal structure fragmented by visas, time zones, and unresolvable grief. The thesis argues that such formal strategies offer a cinematic language capable of expressing what escapes conventional narrative: the silent emotional labor and epistemic gaps faced by those suspended between cultures. Ultimately, the work positions cinema as a counter-archive—one that preserves fleeting affective states and offers critical interventions into how displacement is both lived and represented
CHINESE WOMEN’S PERSPECTIVES IN METAPHORICAL NARRATIVES: EXPLORING IDENTITY, GROWTH, AND SOCIETAL EXPECTATIONS THROUGH ILLUSTRATION
Get PDFThis thesis explores the struggles and growth of Chinese women through metaphorical narratives, focusing on how they navigate societal expectations, gender inequality, and personal identity. First, it examines the importance of metaphor and anthropomorphism in storytelling. It analyzes how these techniques are used to address women\u27s issues. Second, it explores the social background of Chinese women, from the May Fourth Movement, which challenged traditional gender roles, to the socialist era’s push for labor equality, and the modern struggles of workplace discrimination and the double burden. Third, it introduces Tortoise on the Way, a visual thesis written and illustrated by the author, which uses metaphor and anthropomorphism to critique societal norms and honor women’s resilience. This research emphasizes the value of storytelling in empowering women and challenging inequality by reclaiming narratives and promoting solidarity
DEVELOPMENT AND APPLICATION OF LOW-COST CARBON DIOXIDE SENSORS IN AN URBAN ENVIRONMENT
Get PDFAdvancements in sensor technology have made air quality monitoring platforms more user-friendly, compact, and affordable. This provides new opportunities to monitor areas of interest in environments previously not investigated. The existing elevated I-81 Viaduct that runs through downtown Syracuse, NY is being demolished to be reconstructed as a ground level community grid. The goal of the study was to develop a network of low-cost air quality sensor units to monitor concentrations of carbon dioxide along the viaduct prior to its reconstruction. Multiple low-cost carbon dioxide sensors were purchased and tested under laboratory and field conditions to determine applicability for continuous deployment in an urban area. The chosen sensor, the Adafruit SCD-40, was compatible with the Arduino microcontroller, reliable, had a compact design, and was simple to calibrate. The sensor unit was deployed at three different elevations on the Syracuse Center of Excellence (CoE) and in five key locations on the ground level along and near the I-81 Viaduct. It was able to operate for extended periods without significant maintenance or observed degradation in performance over time. The main issue was solar panel effectiveness and consistent power supply. The results demonstrated clear diurnal patterns of CO2 concentrations at all locations. Increased plant growth at the green roof of the SyracuseCoE and the onset of summer denoted more pronounced diurnal range at the CoE sensors on the vegetated roof and the street sensors, respectively. The average CO2 concentration on the upper roof of the SyracuseCoE was the lowest among all sensors deployed at the building. The ground level CO2 concentrations along the viaduct were highest at the location nearest to the intersection of the two highways, I-81 and I-690, although a statistically significant correlation was not determined with the average annual daily traffic Overall, this work could serve as a baseline for atmospheric CO2 concentrations in the city of Syracuse prior to the I-81 Viaduct Project and contribute to general understanding of low-cost sensor networks in urban environments