Economics Commons^™

A Veblenian Approach To Chaos Theory, Isaiah Henry

Hatfield Graduate Journal of Public Affairs

This paper provides a comparative analysis of Veblen's belief in disequilibrium, the field of chaos theory, and how these two frameworks connect. We explore the similarities and differences between Veblen's theories and the principles of chaos theory, including their shared emphasis on complexity and unpredictability. By analyzing the connections between Veblen's economic theories and chaos theory, we can gain a deeper understanding of the nature of disequilibrium and the complex forces that shape our world.

Reducing Carbon Emissions Through Sustainable Food Consumption: Applying An A-S-I Framework On Beijing Residents, Xuan Yang, Jiaxin Zou, Jingyao Gao, Shu Yang

Student Publications

The food sector represents one of the largest contributors to global climate change, making it urgent for the public to transform their food consumption behavior. However, food consumption behaviors that can facilitate carbon reduction, and how to classify these behaviors from the perspective of behavioral science, have not been deeply explored. This study pioneers a novel categorization of carbon-mitigating food consumption behaviors based on an A-S-I framework (i.e., “Avoid” food loss and waste, “Shift” to low-carbon alternatives, and “Improve” dietary structure). Such a classification not only encompasses the full spectrum of emission-altering behaviors but also enables identification of common determinants …

Welfare Implication Of Alternative Tax Rates Adjustment Policy In Nigeria: A Dsge Analysis, Umar B. Ibrahim, Isah F. Abubakar

CBN Journal of Applied Statistics (JAS)

This study sets out to determine the desirable policy adjustment in the tax rate for Nigeria that ensures the least welfare cost. A calibrated small open-economy New Keynesian Dynamic Stochastic General Equilibrium (NKDSGE) model of the Nigerian economy is applied to achieve this objective. Within this framework, we examined the impact of an increase in value-added tax (VAT) rate from 7.5 to 15 percent on key macroeconomic variables relative to the impact of an increase in company income tax (CIT) rate from 30 to 35 percent on macroeconomic variables. Furthermore, we examined the welfare costs of the increases in the …

From Neural Networks To Large Language Models: Innovations In Financial Ai, Mathematical Reasoning, And Structured Data Representation, Junyi Ye

Dissertations

This dissertation explores the evolution and application of artificial intelligence techniques across three critical domains: financial modeling, mathematical reasoning, and structured data analysis. The dissertation presents seven research projects that chart a progression from specialized neural architectures to sophisticated large language models (LLMs), contributing novel methodologies and frameworks at each stage.

In the financial domain, the research first introduces TS-Mixer, a MLP-based architecture for time-series forecasting that captures both feature relationships and temporal dependencies through a simple yet effective design, outperforming more complex models in S&P500 index prediction. The dissertation then presents DySTAGE, a dynamic graph representation learning framework that …

Integrating A Stakeholder-Centric Approach Into Dynamic Adaptation Policy Pathways For Equitable Coastal Flood Risk Management In East Boston, Shailee M. Desai

Graduate Doctoral Dissertations

This research aims to illustrate a methodology incorporating diverse stakeholder values in adaptation planning to promote equitable outcomes using a hypothetical case study of the Lower Border Street area in East Boston, using the Dynamic Adaptive Policy Pathways (DAPP) framework for managing coastal flood risk. It offers three significant contributions to the field of adaptation planning: (i) It demonstrates how to integrate a stakeholder-specific assessment within the DAPP framework and illustrates individual impacts to a variety of stakeholders, including high- and low-income residents, commercial actors, government actors, and coastal landowners hoping that the planning process remains transparent and motivates local …

First Annual Advances In Business Education Conference 2025 Proceedings, Kelsey Metz, Joshua Ray

Advances in Business Education (ABE) Conference Proceedings

Conference Overview: The First Annual Advances in Business Education (ABE) Conference was held on May 16, 2025, at Lincoln Memorial University in Harrogate, Tennessee. Hosted by the LMU School of Business, the ABE Conference was established to promote teaching excellence through innovation and collaboration in business education. With a focus on fostering meaningful dialogue among educators, researchers, and students, the conference welcomed participants from across disciplines and institutions. The event was structured around three key tracks:

Pedagogy & Teaching Excellence: Showcasing innovative teaching methods and strategies for enhancing student learning and engagement.

Business Research: Presenting research focused on advancing knowledge …

Who Owns The Wind: The Absence Of Community Wind Farms In California, Sky Berry-Weiss

Master's Projects and Capstones

Community ownership structures for wind farms have been around for decades, particularly in European countries, due to high socioeconomic benefits. Given these significant benefits, one might expect community wind to thrive in the United States—especially in a state like California, which prides itself on progressive climate policy and renewable energy leadership. Yet utility-scale community wind remains largely absent from research on California’s energy system, raising questions about its existence in the state. To pinpoint how many utility-scale community owned wind farms are in California, this study surveys every operational wind turbine in the state. After classifying each wind farm by …

Independent Vs. Signed Musicians: Does Thier Status Affect Their Success?, Zachary Vincent

Honors Projects in Mathematics and Economics

As technology has advanced and become more widely available, and as the public learns more about the recording industry and its workings, more musicians are choosing not to sign with record labels, becoming independent musicians. This now raises the question: does a musician’s status of independent or signed determine their level of success? It has been previously found that independent musicians have a more difficult time competing with signed musicians due to the resources provided by record labels and the way labels negotiate with large streaming platforms, giving signed labels more opportunities to be seen in the public eye, but …

Recent U.S. Government Policy Literature On Critical And Strategic Minerals, Bert Chapman

Libraries Faculty and Staff Scholarship and Research

Critical and strategic minerals have become increasingly important in U.S. government civilian and military policymaking in recent years. This is demonstrated by the heavy use of such minerals in many critical civilian and military infrastructures. This work will discuss how this subject has been addressed in laws, presidential documents, and works by government agencies along with congressional oversight committees and support agencies. It will stress how the United States is heavily dependent on strategic minerals from adversarial foreign countries such as China and will examine U.S. efforts to increase its ability to produce such materials in the United States by …

Reinforcement Learning, Modeling Markets, And Professional Basketball Free Agency, Jacob Cohn

Computational and Data Sciences (PhD) Dissertations

This dissertation presents a reinforcement learning-based approach to modeling and optimizing decision-making in professional basketball free agency and related economic environments. A Markov Decision Process (MDP) framework is introduced to capture the strategic interactions of NBA teams bidding for free agents under budgetary and roster constraints. To address computational scalability challenges, a reinforcement learning (RL) environment is developed, leveraging Proximal Policy Optimization (PPO) to approximate optimal policies for team decision-making.

Empirical results demonstrate that the RL agent successfully learns strategic bidding behavior that aligns with dynamic programming benchmarks in simplified settings while scaling effectively to larger, intractable environments. The study …

The Impact Of Corporate Profits On Gdi Estimates: Forecasting And Data Revisions, Peterson Haas

Honors Theses

The National Income and Product Accounts (NIPAs) produced by the U.S. Bureau of Economic Analysis (BEA) provide key measures of U.S. economic activity, including gross domestic product (GDP) and gross domestic income (GDI). Although conceptually equivalent, GDP and GDI often diverge due to differences in source data and revision timing. This study focuses on corporate profits—a small but volatile component of GDI that is frequently revised, especially during the BEA’s annual (A1) and benchmark (C1) revisions. I examine how revisions to corporate profits influence GDI revisions and whether they can improve real-time estimates of GDI. First, I document the size …

Mortgage Default Classification Modeling For Variable Analysis, Brendan R. Goggins

Honors College Theses

The financial crisis of the early 2000’s is a prime example of the severe consequences that mortgage default and borrower insolvency can have on economies at large. Mortgage default specifically is a prime case with the popularization of mortgage backed securities and the commonality of this loan structure. Multiple hypotheses and models have been formed to understand the reasons, causes, and consequences of mortgage default. This paper uses both machine learning and statistical classification models to inform an understanding of the variables most significant and impactful to the default outcome of mortgages. Consideration is given to both loan-level microeconomic variables …

Does Better Firm Performance Imply Better Management And Esg Scores?, Shawn Lisann

Research Symposium

No abstract provided.

2025 Acssc Program, Acssc Planning Committee

Annual Celebration for Student Scholarship and Creativity

No abstract provided.

Climate Change Adaptation Through Economic Democracy, Shriraksha Mohan

Best Integrated Writing

Mohan investigates and combines three different areas of literature and social movements to discuss the problem of climate change and economic adaptation. The value of this work is that it can be used to communicate among three independent types of social movements and inquiries. This can strengthen and connect dispersed yet overlapping efforts in addressing work issues, resource utilization, economic governance and participation, and ecological problems economies face today.

Skating For A Payday: Analyzing Nhl Player Performance In Contract Years, Mike Anthony Dibenedetto

Honors Projects in Economics

This research investigates the contract year phenomenon in the National Hockey League (NHL) by analyzing player performance during contract years rather than salary outcomes. Through an extensive literature review and empirical analysis, I examine whether NHL players exhibit statistically significant differences in performance during the final year of their contracts. Drawing from a broad range of studies on performance motivation, team systems, free agency, arbitration rights, and the role of advanced analytics, this paper synthesizes existing theories with new regression-based evidence.

Using a dataset of 2,717 player-season observations, I evaluate the effect of contract year status on key performance metrics, …

Statistical Inference For Noisy Matrix Completion Incorporating Auxiliary Information, Shujie Ma, Po-Yao Niu, Yichong Zhang, Yinchu Zhu

Research Collection School Of Economics

This article investigates statistical inference for noisy matrix completion in a semi-supervised model when auxiliary covariates are available. The model consists of two parts. One part is a low-rank matrix induced by unobserved latent factors; the other part models the effects of the observed covariates through a coefficient matrix which is composed of high-dimensional column vectors. We model the observational pattern of the responses through a logistic regression of the covariates, and allow its probability to go to zero as the sample size increases. We apply an iterative least squares (LS) estimation approach in our considered context. The iterative LS …

Analysis Of Systematic Trade-Offs Between Military And Healthcare Expenditure Alongside Gdp Growth Of Select Asian And Western Exporting Economies In The 21st Century, Rahul Balamurugan, Carlos Gershenson, Preethi Nanjundan, Hiroki Sayama

Northeast Journal of Complex Systems (NEJCS)

This study explores the complexity in the trade-offs between military expenditure, healthcare expenditure, and GDP growth across select Asian nations and major weapon-exporting countries, examining how nations allocate finite resources between national security and human well-being over the past two decades. Using a systems science approach, the research integrates Granger causality testing to analyze temporal and directional relationships among GDP growth, military expenditure, and healthcare expenditure, uncovering their dynamic interdependencies. The methodology includes trend and slope analysis, Granger causality testing, outlier detection, and clustering to identify heterogeneity in resource allocation strategies. Developed, weapon-exporting nations exhibit complementary trends, with strong causality …

Do “Say-On-Pay” Votes Affect M&A Decisions?, Shantanu Dutta, Micah S. Officer, Ruixiang Wang, Pengcheng Zhu

Finance Faculty Works

This paper demonstrates that firms receiving above-industry-average support in their “say-on-pay” (SoP) votes engage in more M&A transactions in the subsequent year. Our empirical findings suggest that high levels of SoP voting support may boost managerial confidence, thereby stimulating increased pursuit of acquisitions. Moreover, we observe that managers garnering higher SoP vote support are more likely to secure shareholders' backing in M&A votes, receive higher compensation in successful deals, and face a reduced likelihood of forced turnover following unsuccessful deals. Additionally, we find that both short-term and long-term M&A performance significantly improves in deals announced by managers receiving higher SoP …

High-Resolution Modeling Of Extreme Heat Events With Socioeconomic Consideration: A Real-Case Wrf-Les Approach, Maryam Golbazi, Frank Liu, Yin-Hsuen Chen, Timothy W. Juliano, Heather Richter

ODU Articles

The overarching goals of this work is to explore best practices for micro-scale modeling of a real case, identify relevant phenomena by using high-resolution modeling, and to explore their implications for public health, and climate resilience strategies in Hampton Roads, VA, USA. This project employs the Weather Research and Forecasting (WRF) model to conduct a comprehensive study of Hampton Roads, utilizing a coupled mesoscale to microscale modeling capable of resolving boundary layer turbulence. This study has three primary objectives: (1) to establish the optimal mesoscale to Large-Eddy Simulation (LES) configurations for complex geographical regions such as the Hampton Roads (HR) …

Digital Platform Transitions In The Finance Industry: Three Essays, Cheryll-Ann Wilson

2025

This three-paper dissertation is motivated by an emerging dichotomy in the financial sector: an increasing use of an open-source digital platform—the Python platform—in an industry that historically has been wedded to proprietary systems.

Chapter 1 is a qualitative pilot study to ascertain which factors are likely to motivate investment professionals to select Python versus other tools and/or technologies. I find that efficiency and access to industry-specific libraries—notably Pandas and NumPy—are significant motivators in their selection of Python over Excel. Chapters 2 and 3 examine the issues through a sequential, exploratory mixed methods approach.

Chapter 2—the qualitative field study—investigates how and …

An Economic And Production Analysis Of Seaweed Farms In California And The Pacific Northwest, Brian Donovan

Cal Poly Humboldt theses and projects

Since the early 2010s, the seaweed aquaculture industry has steadily expanded in the United States, with states like Alaska, Maine, Hawaii, and Connecticut leading the way in the development of this emerging sector. However, information gaps remain concerning certain aspects of the domestic seaweed aquaculture industry. The purpose of this study was to examine the status of the seaweed aquaculture industry along the West Coast of the United States; specifically in the states of California, Oregon, and Washington. Seaweed farmers in these states were invited to voluntarily complete surveys asking important production, economic, and commercial questions regarding their operations. Data …

Hunting And Fishing Ceos: Environmental Plunderers Or Saviors?, Thomas Covington, Steve Widler, Keven Yost

Finance Faculty Works

CEOs who participate in hunting and fishing benefit by appreciating natural environments and permanently consuming natural resources. We examine whether CEOs who hunt and fish make different environmental decisions and find that firms led by CEOs who obtain the most hunting and fishing licenses have lower environmental performance as measured by MSCI-KLD. This effect is strongest in the environmental category of climate change but also extends to pollution, waste, and the protection of natural capital. Furthermore, firms led by CEOs with the most hunting and fishing licenses are significantly more likely to pay a regulatory settlement for an environmental regulatory …

Covariance Matrix Forecasting Of Equity Portfolios, Michael Nebor

Graduate Research Theses & Dissertations

This dissertation consists of two papers. The first paper introduces DCC-SVR, a hybrid Dynamic Conditional Correlation (DCC) and Support Vector Regression (SVR) method of forecasting the covariance matrix. This paper shows that DCC-SVR is able to outperform the traditional methods of DCC and rolling historical on multiple data sets. Performance is shown for both standard GARCH and GJR-GARCH methods. This paper also analyzes performance when dimensions are increased to 49 dimensions and when an application using equal weighted portfolio allocation is used.

The second paper introduces a covariance matrix forecasting method based on copula-GARCH simulated returns. The accuracy of this …

Efficient Algorithms For Nearest Correlation Matrix Computation With Missing Data, Ibrahim Eniola Oyeyinka

Graduate Research Theses & Dissertations

This thesis investigates efficient algorithms for computing the Nearest Correlation Matrix (NCM) under incomplete financial data. Correlation matrices are vital in portfolio optimization and risk management, yet empirical estimates often violate symmetry, positive semidefiniteness, and unit diagonal conditions due to missing observations. Two projection-based methods are analyzed: the Modified Alternating Projections (MAP) and Anderson Acceleration (AA). Theoretical analysis using convex optimization and normal cone characterization supports numerical evaluation on synthetic and real-world stock-return matrices (550×550, 2020–2025). Missing data are modeled through Missing Completely at Random (MCAR) and Not Missing at Random (NMAR) mechanisms. The results show that AA converges faster …

A Modern Optimization Approach With Data-Driven Analytical Modeling For The Healthcare Business Segment (Hbs) From The S&P 500, Aditya Chakraborty, Chris Tsokos

Epidemiology, Biostatistics, & Environmental Health Faculty Publications

Introduction: The S&P consists of eleven business segments, which are classified according to the type of industry. The current study focuses on developing a non-linear analytical model for the Healthcare Business Segment (HBS) of the S&P 500, as a function of different economic & financial indicators. Materials and Methods: The analytical model used six financial indicators together with four economic indicators to predict the weekly average closing price (WCP) of HBS stocks. Johnson’s SB transformation corrected skewness, while desirability-based optimization identified indicator values maximizing WCP. The model’s performance and generalizability were validated through repeated 10-fold cross-validation. Results: All attributable contributors …

Maximum Trimmed Likelihood Estimation For Discrete Multivariate Vasicek Processes, Thomas M. Fullerton Jr., Michael Pokojovy, Andrews T. Anum, Ebenezer Nkum

Mathematics & Statistics Faculty Publications

The multivariate Vasicek model is commonly used to capture mean-reverting dynamics typical for short rates, asset price stochastic log-volatilities, etc. Reparametrizing the discretized problem as a VAR(1) model, the parameters are oftentimes estimated using the multivariate least squares (MLS) method, which can be susceptible to outliers. To account for potential model violations, a maximum trimmed likelihood estimation (MTLE) approach is utilized to derive a system of nonlinear estimating equations, and an iterative procedure is developed to solve the latter. In addition to robustness, our new technique allows for reliable recovery of the long-term mean, unlike existing methodologies. A set of …

Climate Migration And Urban Survival: Evidence From Chittagong’S Slums, Mohammad Nur Nobi

Graduate Research Theses & Dissertations

This study examines the impact of climate change on rural-to-urban migration in Chittagong, Bangladesh. Based on a primary survey of 400 respondents across 35 slums in the country's second-largest city, the analysis employs two estimation methods: a multinomial logit model to assess the influence of climate-related factors on migration decisions, and a logit model to evaluate the impact of migration on the living conditions of migrants. The results show that individuals involved in ‘agriculture and daily labor’ are most likely to migrate. Compared to the base category (‘Other Reasons’) for migration, the odds ratios for ‘floods’, ‘droughts’, and ‘better job …

Capital Structure Models And Contingent Convertible Securities, Di Meng

Theses and Dissertations (Comprehensive)

The 2007-09 financial crisis showed financial institutions are vulnerable during distressed times. As an alternative resolution to a government bail-out, contingent convertible securities (contingent capital or CoCos) were proposed by various researchers. CoCo is a hybrid capital security that converts from a bond to common equity when a pre-determined event occurs. The loss absorption mechanism of CoCo is essential to the financial health of a bank during a crisis as it provides an instant capital infusion when public capital is difficult to access.

In this thesis, we first implement a methodology to calibrate capital structure models for large Canadian banks. …

The Gender Wage Gap In An Online Labor Market: The Cost Of Interruptions, Abi Adams, Kotaro Hara, Kristy Milland, Chris Callison-Burch

Research Collection School Of Computing and Information Systems

This paper analyses gender differences in working patterns and wages on Amazon Mechanical Turk, a popular online labour platform. Using information on 2 million tasks, we find no gender differences in task selection nor experience. Nonetheless, women earn 20% less per hour on average. Gender differences in working patterns are a significant driver of this wage gap. Women are more likely to interrupt their working time on the platform with consequences for their task completion speed. A follow-up survey shows that the gender differences in working patterns and hourly wages are concentrated amongst workers with children.