More Education Yet Rewarding Capital? China’s Mass College Expansion and the Decline in Labor Share
This study examines how China’s massive college expansion affected the functional distribution of income between labor and capital. Using firm-level panel data from 1998 to 2007 and a difference-in-differences strategy dependent on cross-industry skill intensity, I find that the surge in college graduates led to a significant 3.71 percentage point decline in the labor share within skill-intensive firms. The analysis demonstrates that this decline was not driven by suppressed wages but by capital deepening. The increased supply of educated labor facilitated a shift toward capital-intensive production technologies. The finding provides causal evidence that the expansion of human capital can accelerate the decline of labor share through capital-skill complementarity.
Regional Disparities in Individual Expenditure: Evidence from China
This paper examines household expenditure disparities in China using the China Family Panel Studies (CFPS). I estimate fixed-effects models of household expenditures on age, health, life satisfaction, number of children, education, region, and GDP per capita. The results show significant regional disparities across the eastern, middle, and western parts of China. Additionally, higher education is associated with a 21.4% increase in expenditures. Life satisfaction, number of children, and GDP per capita are positively related to spending, while age has a negative but diminishing effect.
[Link]
The Effect of Cigarette Taxation on Cigarette Consumption
This study employs a difference-in-differences method with a time-series design to evaluate the impact of a cigarette tax increase on consumption implemented in New York in 2000. Cigarette consumption in New York was predicted to significantly decrease in 2001 relative to 1999, compared to New Jersey. After adjusting for education levels, it shows that the cigarette tax increase in New York had a stronger impact for those with lower education attainmemt.
Prescription Drug Monitoring Programs: Evidence on Opioid-Related Hospitalizations
This paper estimates the effects of Prescription Drug Monitoring Programs (PDMPs) on nonfatal opioid-related hospital admissions using administrative discharge records from the Healthcare Cost and Utilization Project (HCUP) National Inpatient Sample (NIS) data from 1998 to 2011. Exploiting within-state variation in PDMP adoption, I estimate a two-way fixed effects model and conduct event-study analyses. The results provide no evidence that PDMPs reduced nonfatal opioid-related hospitalizations.
(Draft available upon request)
Identifying the Basis of Disproportional Minority Confinement
This study investigates the foundations of disparate minority confinement within the juvenile justice system (JJS) and examines whether patterns of Disproportionate Minority Contact (DMC) shifted following the emergence of the Black Lives Matter movement in 2013. Using arrest and confinement data from 1997 to 2019, I analyze how racial disparities in arrests contribute to disparities in detention and commitment across crime types. The findings indicate that the share of detention disparities explained by arrest disparities has remained relatively stable over time. The result also shows that by 2019, racial disparities in arrests accounted for 18% more of the racial disparity in commitments than in 1997, suggesting a decline in discrimination against Black youth in post-arrest processing.
(Draft available upon request)
Life-Cycle Patterns of Individual Debt Decisions
Lead researcher: Prof. Giovanni Gallipoli
This project examines individuals’ optimal debt decisions over the life cycle using household-level data. As a research assistant, I analyzed the Survey of Consumer Finances (1990–2020) in Stata to document household debt patterns by age, ethnicity, and decade. Moreover, I documented stylized facts to provide the empirical foundation for subsequent model development on optimal debt holdings.
Industrial Structure Change, Production Technology, and Fertility Choice
Lead researcher: Prof. Giovanni Gallipoli
This study examines how the industrial structure change driven by technological advancement reshapes gender segregation in the labor market, and how such labor market shifts influence household fertility choices. As a research assistant, I collected and organized historical versions of the Occupational Information Network (O*NET) data, matched release years to corresponding survey questions for comparative analysis, and created a detailed reference sheet documenting survey identifiers, sources, and metadata.
Restricted Paths and Mission Impossible: Gender Views
Lead researcher: Prof. Heather Sarsons
This study investigates gender differences in labor market outcomes by investigating how societal beliefs shape the perceived acceptability of men’s and women’s behaviors. As a research assistant, I conducted an extensive literature review in economics and sociology on how gender norms and social expectations influence men’s education and college major choices. Moreover, I synthesized findings on societal gender views to support future theoretical framing and empirical strategy.
Growing Miracle of East Asia
Lead researcher: Prof. Réka Juhász, Prof. Nathan Lane
The last few decades of the twentieth century witnessed rapid and sustained economic growth across several East Asian nations, where industrial policy played an important role in explaining such a trajectory. During my summer research internship in the Industrial Policy Research Group, I collaborated on processing and analyzing international trade patterns for 10 East Asian countries from 1870 to 2013, covering over 120 industry categories. In addition, I contributed to data entry validation and coded East Asian industrial policies based on government policy records, creating a structured reference for subsequent empirical analysis of policy impacts on trade and growth.
Instrumental Variable Design and Empirical Evaluation
Lead researcher: Prof. Jonathan Graves
As a team member of COMET (Creating Online Materials for Econometric Teaching) at the University of British Columbia, I contributed to the development of hands-on learning modules that connect econometric theory with real-world applications. My work focused on instrumental variable (IV) analysis, where I implemented IV methods in R, compiled a step-by-step guidebook, and designed a training packet for second-year economics students.
Benchmark Analysis of Sequential Penalty Kickers in Games
Lead researcher: Prof. Hao Li
This project investigates how the sequencing of penalty kickers influences outcomes in professional soccer under high-pressure and low-pressure game contexts. As a research assistant, I evaluated the preliminary benchmark analysis comparing kicker sequence results across pressure and non-pressure games, and contributed to the quantitative modeling by replicating the first stage of the game based on official penalty kick rules.
Economic Development and Fertility: Impact of the Universal Two-Child Policy
This project examines the relationship between economic development and fertility in China under the universal Two-Child Policy. Using provincial data on key macroeconomic indicators (nominal GDP per capita, average wages, disposable income, unemployment, and inflation), I examined regional development patterns across 31 provinces and estimated birth rates using regression models. The results show that GDP is positively associated with birth rates, whereas higher disposable income and inflation are negatively correlated with fertility. The analysis finds no statistically significant evidence that the universal Two-Child Policy increased birth rates.
[Link]
Chemical Signatures: Predicting Wine Ratings Using Machine Learning Methods
This study investigates an algorithm for predicting white wine quality using a K Nearest Neighbors (KNN) classification approach. Five chemical attributes were selected as the main criteria based on their relevance to perceived wine quality: volatile acidity, chlorides, density, pH level, and sulphates. The project evaluates how effectively KNN can model sensory quality using measurable chemical traits and offers insight into the potential of data-driven methods for quality assessment in enology.
[Link]
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