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CECL Adoption and the Contractual Usefulness of Accounting Earnings in Bank CEO Compensation
No full textThe adoption of the Current Expected Credit Losses (CECL) model, a new methodology for accounting for expected credit losses, has significantly increased bank earnings volatility. Using a difference-in-differences design around adoption, we examine how more volatile earnings impact CEO compensation design. We find that post-CECL, bank CEO pay becomes less sensitive to earnings, but more sensitive to other performance measures, such as stock returns and revenues. Additionally, total executive compensation increases, consistent with the higher risk premia demanded by bank executives. Overall, our results suggest that compensation committees view accounting earnings as having lower contractual usefulness for incentives after CECL
Comparative Study On Rocking Dynamics And Energy Dissipation Of Rigid Bodies: A Microscale Framework
No full textThis thesis presents a microscale framework for investigating the seismic stability of bridge pier structures using the discrete element method (DEM), with a focus on rocking isolation mechanisms and addressing the limitations of traditional methodologies in capturing the complex dynamics of earthquake-structure interactions. The study expands on a careful assessment of an experimental data from a granite stone to a single-bridge-pier model, revealing structural instabilities when subjected to seismic excitation. DEM simulations and analytical approach are systematically validated capturing the complex dynamics of bridge pier interaction. The study demonstrates the effectiveness of rocking isolation through a comparative analysis of acceleration and angular velocity under varying seismic intensities and frequencies, with acceleration reductions up to 70% for piers and 60% for decks in high-intensity scenarios aiming the potential of rocking isolation as a viable seismic mitigation strategy. The study monitors the structural response, contact mechanics and energy dissipation of the pier deck system. The application of the DEM Hertz contact model advanced the analysis of bridge pier and deck interactions under seismic loads, providing new insights into the detailed behavior of rocking bridge piers and their potential for seismic isolation. This work contributes to seismic analysis techniques and predictive models that captures the complex dynamics of earthquake in seismically active areas
Enlivened Worship with the Divine: Evaluation and Innovative Application of the Liturgical Arts for Worship Renewal
Get PDFLiturgical arts are meaningful resources and vessels for reclaiming and renewing the storytelling abilities of dynamic worship. This thesis explores a strategic evaluation of liturgical arts through the foundational and relational subjects of theology, ritual studies, and liturgical theology. Through the Holy Spirit, liturgical arts have formative powers that lead congregations into a deeper meeting with God—sending them forth as renewed signposts of Christ’s transcendence. They provide the space where pain and brokenness meet hope and grace for the renewal of the world.
This thesis examines those powers in combination with a foundational and contextual evaluation to restore and apply innovative liturgical art that allows for the possibility of a vibrant and active dialogue between worshipers and the Triune God. A series of liturgies are included as examples highlighting these powers. Through a continuous process of evaluation and innovative application of the liturgical arts, a worshiping community has a foundational strategy to actively maintain, reimagine, and renew an ever-evolving, enlivened worship experience that intersects with the Divine
The Taxation of Robots and Its Global Challenges
No full textRobots are changing the world. In the past decade, we have already seen robots perform medical procedures, drive cars, serve as virtual assistants, analyze financial data, perform legal research, and win Jeopardy. These examples illustrate powerful new forms of automation that go beyond manual labor and assembly lines into tasks that once seemed impossible to automate. This is just the beginning. Robots now have the potential to invade almost all sectors of the economy and are expected to do so faster than previous technological changes. Many fear that millions will lose their jobs, leading to massive technological unemployment. To address these anticipated problems, there have been calls worldwide to implement a tax on robots.
This chapter explores the reasons behind these calls and whether policymakers should pursue a robot tax. It provides an overview of the international implications of increased robot use and critically analyzes robot tax proposals from an international perspective, highlighting negative policy implications and practical issues. After demonstrating why a robot tax is not the best solution, the chapter suggests alternative actions nations should consider to address the challenges of the new automation era. As Erik Brynjolfsson observes, “This is a moment of choice and opportunity. It could be the best 10 years ahead of us or one of the worst because we have more power than ever before.” Thus, while a robot tax may not be the optimal approach, policymakers have a crucial responsibility to acknowledge the potential of robots and address the associated risks and challenges
Salt & Sand: Deep History in the Permian Basin
No full textThis dissertation approaches the environmental history of the Permian Basin of southeastern New Mexico and West Texas through a “geo-regional” framework. In doing so, it contends that key aspects of the region’s social, political, and economic development are directly tied to its mineral resources and the geological processes that deposited them. In contrast to traditional environmental analyses of the Permian Basin, which typically focus on the area’s prodigious hydrocarbon reserves, the present study instead highlights a more common—but no less important—mineral: salt. Organized in three parts, it traces the evolving functions of this mundane resource through the annals of deep time. In addition to outlining each of the project’s chapters, the Introduction offers a meditation on the cultural characteristics of the Permian Basin. Part I, “Deposition,” explores the intellectual construction of the expanded geologic timescale (which allowed for human understandings of earth’s antiquity), establishes the historiographical and methodological underpinnings of “geo-regionalism,” and briefly chronicles the Permian Basin’s geological and archaeological pasts. Part II, “Extraction,” narrates the twentieth-century discovery of potash in the salt beds of southeastern New Mexico and the influx of mining companies that transformed Carlsbad, New Mexico from a sleepy agricultural village into a blue-collar, industrial city of national significance—as well as the oft-overlooked role organized labor played in that dramatic metamorphosis. Part III, “Insertion,” examines the collapse of the potash industry’s monopoly on the mineral commodity’s North American market, which led the local community to embrace novel utilizations of the salt deposits—initially as a subterranean testing medium for atomic explosives research and eventually as a controversial permanent geologic repository for transuranic nuclear waste. The Epilogue spotlights current threats to the environmental and economic health of this “geo-region” and propels the study to the other end of the chronological spectrum, detailing long-range plans for warning markers intended to communicate the facility’s hazardous nature 10,000 years into the deep future
“It’s Hard to Quantify Community Togetherness”: Exploring The Evolution Of Data Science Practices And Uncovering Critical Tensions
No full textThis dissertation explores the integration of data science practices with social justice principles, particularly within the context of food justice. The research is driven by two primary questions: (1) What are the differences in data science practices when applied to social good projects? (2) What critical tensions arise when balancing simplicity and complexity in data science for social good?
The findings explore the differences in data science practices and highlights critical tensions such as simplicity versus complexity, balancing constraints, and addressing food justice through data science. These tensions are summarized to provide insights into the stances adopted by participants. Overall, this dissertation contributes to the understanding of how data science can be harnessed to promote social justice, offering valuable insights for educators, practitioners, and researchers in the field
Bayesian and Deep Generative Modeling in Immunology
Get PDFDue to the accumulation of a large volume of data of different natures such as sequencing data, proteomics data, and clinical data, statistical methods and deep learning algorithms have become increasingly important in the field of immunology. By leveraging the diverse datasets as well as interdisciplinary knowledge from areas like biology and public health, these quantitative methods have revolutionized this field by providing powerful tools for data analysis, modeling, and prediction. This has led to a deeper understanding of the immune system, accelerated the development of novel therapies, and paved the way for personalized and precision medicine approaches in immunology.
In this dissertation, we attempt to utilize Bayesian modeling techniques in conjunction with deep generative models to address emerging issues in immunology. Specifically, three models based on variational Bayes methods are devised for CyTOF data simulation, TCR-pMHC binding affinity prediction, and exploratory CyTOF data analysis. In chapter 2, Cytomulate, the first comprehensive simulation tool tailored for CyTOF data is proposed. pMTnet omni, which is detailed in chapter 3 carries the capability of differentiating binding and non-binding TCR-pMHC pairs. Finally, introduced in chapter 4, CytoOne provides a unified probabilistic framework for most CyTOF data analysis tasks
Three Essays in Macroeconomics
Get PDFThis dissertation comprises three chapters, with the first two focusing on the labor market and the third examining the impact of uncertainty on asset prices. These topics are highly relevant to current literature and have significant policy implications.
The primary purpose of the first two chapters is to address the Shimer puzzle, which suggests that technology shocks cannot account for the high variations observed in the labor market. Understanding the underlying sources that can explain this puzzle is crucial as it helps us comprehend factors affecting job creation and the unemployment rate. Moreover, labor market fluctuations play a vital role in predicting business cycles and evaluating interest rates.
Labor market conditions have been emphasized in recent economic policy discussions. They are a key consideration during the process of raising interest rates in 2021 and have been mentioned in every Federal Open Market Committee (FOMC) meeting and public speech since the beginning of 2024 by Federal Reserve Chairman Jerome Powell. Beyond the impact of labor market conditions on monetary policy, research on the labor market also provides insights into other government policies, such as those related to wage rigidities, unemployment benefits, or mismatches between firms and the unemployed.
Given the importance of labor market research and the limitations of previous studies, Chapter One examines the impact of the discount factor in the labor market. We emphasize that this factor can influence both households\u27 decisions and firms\u27 hiring decisions. In Chapter Two, considering that business formation is one of the major driving forces of aggregate fluctuations and that credit constraints limit firms\u27 borrowing capacity to hire, we integrate these two aspects into one real business cycle model. Furthermore, the third chapter is closely related to the preceding two chapters, as variations in the labor market are also a source of uncertainty and both the labor market and asset prices are influenced by monetary policies and business cycles.
In the first chapter, we explore the determinants of co-movements in the labor market and the stock market, moving beyond previous literature focusing on technology shocks. We develop a real business cycle model incorporating labor market frictions. We also employ the Epstein-Zin utility function and convex adjustment costs for capital, standard in the asset pricing literature, to better capture the role of the discount factor. Additional considerations include unemployment benefits and matching efficiency, as well as government spending. To examine the impact of wage rigidities, we compare Nash bargaining and alternative offer bargaining mechanisms. We also examine different ratios of unemployment benefits to wages to address the lack of consensus in the existing literature. Using Bayesian estimation, we quantify the contributions of each source to the variations in the labor market and the stock market. The findings indicate that unemployment benefits are the primary driver of labor market fluctuations, while the discount factor explains most variations in the price-dividend ratio. Our findings also reveal that the impact of these shocks varies depending on the presence of wage rigidities and the ratio of unemployment benefits to wages.
In the second chapter, we integrate credit constraints and firm dynamics into a real business cycle model to explore how these two frictions explain labor market fluctuations. By considering the direct impact of credit constraints on job creation as well as the direct effects of firm dynamics on both job creation and destruction, our study addresses research gaps that have previously focused on analyzing these frictions in isolation. We utilize the enforcement constraint to model credit frictions, while the endogenous number of firms depends on the number of varieties produced. We find that productivity shocks are amplified due to credit frictions and firm dynamics.
In the third chapter, we examine the impact of uncertainty on asset prices using the macroeconomic uncertainty index as a proxy. However, previous literature has focused on investigating these effects in the structural vector autoregressive (VAR) model. Utilizing a structural VAR model to analyze the effects of the uncertainty index is inadequate due to its inability to capture nonlinearity and time-varying variance in the uncertainty index. To address this gap in the literature, we employ a time-varying VAR model with stochastic volatility to determine whether the impacts of uncertainty shocks differ across business cycles and exhibit asymmetric impacts. The findings show adverse effects of uncertainty shocks in both models, with varying magnitudes of rebound and overshoot across different business cycles. Furthermore, the findings do not provide evidence of the asymmetric effects of uncertainty shocks
Ethics of Innovation: A Framework for Responsible Innovation Governance
Get PDFOver the past several years, startups that once seemed destined for greatness have failed or collapsed because of fraud committed by the founders. Most notable are the Theranos and FTX business collapses, which culminated in the convictions of two infamous entrepreneurs, Elizabeth Holmes and Sam Bankman-Fired, respectively. Startup innovators are not alone when it comes to morally dubious behavior. According to Retraction Watch, nearly 5000 papers published in science & engineering journals were retracted in 2022. Research misconduct allegations eventually led to the resignation of Stanford University President Marc Tessier-Lavigne in July 2023. The research scandal at Stanford received lots of public attention. Absent such public scrutiny, however, organizations are slow to act on allegations of research falsification. This raises several important questions: are these occurrences becoming more frequent? What governance frameworks are available to effectively detect and prevent such misconduct and fraudulent behavior? This Essay examines the current business ethics and corporate governance framework applicable to innovation, argues that it lacks sufficient safeguards to prevent misconduct and promote responsible practices. This Essay offers a two-pronged approach to address the ethical void in innovation. First, the implementation of stricter oversight by federal agencies (such as NSF or NIH), including penalties for non-compliance. Second, the legal profession must play a more active role in shaping and advising on ethical frameworks for responsible innovation. Lawyers can play a crucial role in evaluating both the risks and benefits of innovation, while also utilizing innovative tools to improve legal service delivery. By combining enhanced oversight with deeper legal involvement, we can create a more robust and comprehensive framework that fosters responsible innovation governance