QMSA Thesis Projects – 2024 Cohort

Xiaolong Bai

Title: Weather Shocks and Stock Market Performance: Insights from China’s Agricultural Sector

In recent decades, global climate change has resulted in a notable increase in the frequency and severity of extreme weather events worldwide, including in China, presenting considerable challenges for agricultural companies. For agricultural companies, these events signify heightened market risks related to production and operations, impacting financial markets. This study employs event study methodology and the Fama–French three-factor model to analyze the abnormal impacts of extreme rainfall and high-temperature events on agricultural stock returns in China from 2013 to 2023. This research concluded a significant negative impact on the stock prices of agricultural companies within a short-term window (11 days) around extreme weather events, especially on the day before the event. Furthermore, the study finds that the market’s reaction varies with the severity of weather disasters. Our research suggests that policymakers should recognize the consequences of such events on the stock market and adopt the following policies: strengthen corporate climate risk management, developing financial products related to climate risk, enhancing climate risk information disclosure, and bolstering government support and policy guidance.

Xintong Cai

Of Sugar and of Bullet: Tracing the consequences of 1740 Batavia Massacre

1740 Batavia Massacre is an extermination against Chinese that happened in 1740 in Batavia, now known as Jarkata, Indonesia. While people hold different opinions about the real cause of the massacre, the Dutch authority has proclaimed that this massacre was an incident randomly. However, it has been widely proposed that the Dutch made this event to maximize the trade profit for the VOC (East India Company). As a main player in the Euro-Asia trade, VOC gained great profit from transporting commodities from Asia to Europe. There are commodities that are closely related to the Chinese group like pepper, and we can see the effect of the massacre by studying the price of commodities that are Chinese-related. We use difference in differences method to study the price of pepper and white pepper, which are commodities mostly related to the Chinese workers. We find that the massacre lead to both the short-term and long-term price increase in pepper, and the profit of VOC increased. This is further verified in historical accounts, which shows that the massacre is hardly an accident with its interests perfectly aligning with the colonizer and the company.

Yuhan Chen

Exploring the Associations of Being Exposed to Positive and Negative Body Talk with Self-Objectification, Appearance Comparison, Body Appreciation, and Emotion Status: Application of a Location-Scale Mixed Model

The purpose of this study was to apply a Location-Scale Mixed Model, which allows for examining how covariates affect both the mean and variance structures, to analyze the impact of body talk on self-objectification, appearance comparison, body appreciation, emotion, and muscle dissatisfaction.

Methods: Data were collected from 120 female undergraduate students by a 7-day Ecological Momentary Assessment (EMA) data collection period. Positive and negative body talks were obtained through binary questions in the EMA questionnaire. Self-objectification, appearance comparison, body appreciation, emotion were measured by Objectified Body Consciousness Scale (OBCS), The State Appearance Comparison Scale (SACS), The Body Appreciation Scale-2 (BAS-2), and International Positive and Negative Affect Schedule Short Form (I-PANAS-SF) respectively.

Results: Exposure to either positive or negative body talk increases the level of self-objectification (b = .15, p = .004; b = .11, p = .037), body comparison (b = .29, p = .002; b = .25, p < .001), and negative emotion (b = .14, p < .001; b = .10, p < .001) at the within-subject level. Exposure to negative body talk decreases the level of Body appreciation (b = -.05, p = .007). The WS (within-subjects) variance model showed that exposure to positive body talk at within-subject associates with greater WS self-objectification variance (b = 0.84, p < .001), greater WS body comparison variance (b = 0.64, p < .001), and greater WS body appreciation variance (b = .60, p = .002); exposure to negative body talk at within-subject associates with greater WS self-objectification variance (b = 0.33, p = .048), greater WS body appreciation variance (b = 1.02, p < .001), and greater negative emotion state (b = 0.59, p < .001).

Conclusion: Being exposed to both positive and negative body talk predicts a lower emotional status and does harm to body image over time, including a decrease in body appreciation, an increase in self-objectification and appearance comparison. Additionally, exposure to both positive and negative body talk at the within-subject level predicts higher WS variance in emotional status, body appreciation, self-objectification and appearance comparison over time.


Kangcheng He

Dependence on Russian Resources and Exchange Rate Fluctuations During the Russia-Ukraine Conflict


This article aims to explore the role played by dependence on Russian resources on the exchange rate of non-belligerent economies, following the Russia-Ukraine conflict. A mixed effect model, which considers both the long-term impact of the conflict itself and the influence of significant sub-events during the conflict, is established to derive the impact pattern of dependency on Russian petroleum, gas, and cereal on exchange rate fluctuations. The model results indicate that dependence on Russian petroleum and natural gas does not have a significant impact on exchange rate fluctuations in the long term, but it is related to a significant depreciation on the dates of conflict-escalating events and economic sanctions. On the other hand, high dependence on Russian cereals is significantly associated with long-term currency depreciation.


Minjun Lee

The Asymmetric Impacts of Economic Policy Uncertainty on Different Types of Stock Volatility

This study investigates the impacts of the Economic Policy Uncertainty Index on different types of stock volatility. We use the standard VAR models between the EPU index and the GARCH volatility of each stock index (large-cap growth, large-cap value, small-cap growth, and small-cap value stocks). We analyze their impulse response functions, especially the responses and accumulated responses of the GARCH volatility of each stock index to the EPU index innovation. The empirical results show that the EPU index influences the volatility of value stocks more than that of growth stocks for both large-cap and small-cap stocks. In addition, small-cap value stocks are affected by the EPU index the most.

Tianyu Qiao

U.S.-China Great Power Competition in Foreign Direct Investment in the Global South: A Cross-Sectoral Study

How does U.S. commercial and political engagement in a developing country impact Chinese strategic investment decision? How does this impact vary across conventional and high- tech sectors? Drawing on previous literature in International Relations and International Political Economy (IPE), I developed and tested three different theories in this essay: 1) great power competition theory and full-out competition; 2) IPE and comparative advantage theory; 3) selective competition theory. Through a gravity model of trade and a novel data set, I find support for the third theory: existing U.S. investments in a conventional sector in a host country diminish Chinese investment incentives. In contrast, U.S. investments in technology-intensive sectors stimulate Chinese investments, resulting in higher congruence in location choices. Geo- strategically, a closer political relationship between the U.S. and a host country decreases Chinese investments, but greater U.S. military involvement in that country stimulates Chinese investment incentives. I argue the higher congruence in U.S.-China foreign investments in a high-tech sector stem from China’s desire to challenge the technological dominance of the United States and its leadership role in the global industrial standards-setting regime. This study contributes to the current literature in international political economy on the determinants of Chinese outward foreign direct investment (OFDI).

Jack Vasilopoulos

A Comprehensive Examination of Public and Private Risk Measures for Distinct Commercial Real Estate Asset Classes: Insights from Mixed-Effects Regressions

This paper employs mixed-effects regression models (MRMs) to examine the multifaceted
components of public and private commercial real estate (CRE) risk. It does so through two
exemplar datasets: public Real Estate Investment Trusts (REITs) and private Commercial
Mortgage Backed Security (CMBS) loans. For public REITs, traditional MRMs investigate the
effects of (1) dividends, (2) market capitalization, (3) acquisitions, and (4) percentage of
unsecured debt on the capitalization rates of varying REIT sectors. For private CMBS loans,
logistic MRMs assess the effects of (1) occupancy-rates, (2) debt-rates, and (3) principal on loan
default and delinquency rates. For both datasets, these risk metrics are implemented as both fixed
and random-effects in order to investigate their net impacts and degree of property-type
heterogeneity; public market analysis also examines within and between-subject effects.

Public results show that the effects of two risk metrics, dividends and market capitalization,
exhibited disparate impacts on the capitalization rates of different REIT sectors. Empirical Bayes
random-effect estimates, for example, show that dividends significantly influence hotel
capitalization rates, while this significance is not observed in the retail sector. Across sectors,
most metrics’ within-subject fixed-effect components yielded statistically significant results,
except for the percentage of unsecured debt. Finally, the significance of acquisition’s
between-subject effect offers evidence of a potential correlation between higher mean acquisition
rates and lower capitalization rates.

Similarly, private market analysis also revealed substantial property-type and region variability
in CMBS defaults. However, logistic MRM results indicate that solely the risk metrics’
fixed-effect components are significant in predicting CMBS default rates, indicating consistent
impacts across sectors. As such, incorporating random-effects for private risk metrics proved
unnecessary, yet property-type clustering remained essential. Overall, this paper underscores the
nuanced nature of CRE risk assessment, arguing for increased consideration of property-specific

Runlin Wang

Adapting to the AI Era: An Analysis of U.S. Public University Course Syllabi and Educational Policies in Response to (Generative) AI Technologies.

My research is essentially driven by a concern regarding the integration of AI guidelines in education, especially given the rapid advancements in (generative) AI tools, as demonstrated by platforms like ChatGPT. This has led to my research question: How are U.S. public universities adapting their educational policies, particularly within course syllabi, to address “AI” and its associated regulations in an ethical manner, especially in guiding instructors and students? In my thesis, I aim to argue that if university-wide guidelines appear to support the usage of generative AI or advocate for its ethical application, then this may be reflected in an overall increased emphasis on AI in course syllabi, which could in turn cultivate a more positive attitude towards AI technology. To investigate my hypothesis, I plan to conduct an in-depth text analysis of selected course syllabi from the University of Michigan. Moreover, it is also important to note that these syllabi may not represent a consistent pattern across different departments within the university. The significance of this research stems from the substantial impact of ChatGPT’s launch in November 2022, which not only captured widespread public interest but also marked an inevitable shift in the educational landscape. As a student witnessing the rising popularity of generative AI among educational fields, I am keen to explore how institutions, instructors, and students are adapting to and managing its widespread influence.

Yuan Yuan 

College Students Mental Health: Provision, Literacy, and Outcomes

Recent years have witnessed a deteriorating trend in mental health, especially on college campuses. While extensive research exists on the utilization of mental health services on campus, few studies have investigated and quantified how the school mental health outreach effort impacts on mental health outcomes, especially through the knowledge and attitudes toward mental illnesses. This thesis presents an empirical study of the causal effect of school provision through mental health literacy (MHL) on mental health. Using data from the Healthy Minds Study spanning from 2017 to 2023, I found that the awareness of mental health outreach efforts improve the mental health status. Specifically, a [10%] * decrease in the probability of depression and anxiety disorders among college students is through the increase in knowledge and beliefs about mental health and mental illness. This study also offers policy implications regarding the psychosocial treatments for the mental health crisis. It suggests that, alongside allocating resources for treating mental illnesses, investing in the public’s perception of mental health is crucial to dissipate stigma and advocate for initiatives promoting self-help and help-seeking behaviors. Specific measurements of MHL are discussed as well.

* This finding is preliminary and subject to change


Rui Zou

Can Digital Finance Promote Enterprise Growth?

The integrated development of the digital economy and real economy is an important trend of future economic development, and digital finance is an important part of the digital economy. It is of great significance to explore the influence mechanism of digital finance on enterprise growth. By integrating financing constraints, capital input, and technological innovation into a unified framework, this study explores the transmission mechanisms of digital finance on Chinese enterprise growth. Meanwhile, based on the empirical framework of Gibrat’s Law, the data of digital finance and listed enterprises from 2011 to 2021 are used to empirically test the correlation between digital finance and enterprise growth. By further examining its influence mechanism, the boundary and scope of the research on the influence of digital finance on corporate behavior and performance are expanded. Different from previous studies, this study focuses on exploring the influence mechanism of digital finance on enterprise growth.

Ziyang Xie

Innovative Recruiting Strategies in Business Schools: Identifying Potential Underperforming Researchers

Victor Vroom’s expectancy theory mentions that an individual’s motivation is driven by the expected outcome. This means that once individuals achieve their goal and receive the expected reward, their motivation—and accordingly their efforts—may decrease, as the goal no longer serves as a motivating factor. Given the unique aspects of tenure as a symbol of job security, recognition of research and teaching quality, and higher reputation, tenure may represent a reasonable target. Once obtaining tenure, professors might experience a decrease in motivation, resulting in reduced research output.


This paper aims to construct a predictive model to identify the level of productivity changes after business school professors achieve tenure. We intend to utilize our predictive results as one of the recruitment criteria for business schools and simulate the implementation effects using counterfactual microsimulations.


Our study is pioneering, with numerous research endeavors focusing on the variations in professors’ outputs before and after tenure, as well as those aimed at identifying factors measuring professors’ research levels. However, few studies have delved into why there is a decline in professors’ outputs post tenure. Furthermore, if a decline in post-tenure output is inevitable, what character traits do professors who experience the least decline possess? After all, regardless of a candidate’s past achievements, the ability to maintain or even enhance accumulated research capabilities is of utmost importance to the institution.


Zoey Zhou

Unraveling the Tricks: An Exploration of the Prevalence and Impact of Deceptive Patterns Across E-Fashion Website Designs.

In the vast landscape of online shopping, we are exposed to an extensive amount of information and stimuli. How much of our decisions to buy are truly rational? Researchers have found that businesses incorporate “deceptive patterns”—tactics of user interface design that leads users to inadvertent actions such as purchasing and subscribing membership—to manipulate our decision makings (Brignull, 2018; Mathur et al., 2018). This study delves into the realm of online fashion websites, scrutinizing the prevalence and impact of these deceptive design strategies. Through a combination of quantitative analysis and in-depth interviews, this paper aims to address four key research questions: 1) What is the prevalence of deceptive patterns on online fashion platforms compared to general shopping platforms? 2) How do the prevalence and characteristics of deceptive patterns vary across online fashion platforms? 3) How do consumers perceive and respond to these design strategies? 4) What are the subsequent impacts of deceptive patterns on consumer trust? Shedding light on both prevalent phenomenon and user perspectives, this research illuminates the role of deceptive patterns in shaping consumer decisions and suggests potential countermeasures.