Research
Research
Information Inequality in College Major Choice
I study disparities in college major choices across students from different socioeconomic backgrounds and analyze their implications for intergenerational income mobility. One potential explanation for these disparities is differential access to information about majors' academic content and personal fit. To explore the role of information frictions on major choices, I use administrative data from the centralized college application system in China. Consistent with the information inequality hypothesis, I document that students of low socioeconomic status (SES) are 21.6% (3.16 percentage points) more likely than their high-SES peers to choose majors that are familiar to them from their high school curricula. Further support for the information inequality hypothesis comes from a survey experiment in which high school students report their expectations about college majors and from information spillovers among high school classmates. To discuss the economic consequences, I calibrate a model of major choice and find that, because of information inequality, low-SES students face higher mismatch rates and lower future incomes than their high-SES peers. Counterfactual analyses indicate that information interventions and affirmative action policies can effectively narrow the income gap across socioeconomic backgrounds.
Internships have become increasingly important for college students, yet much remains unknown about how higher education institutions can be structured to support internship participation. In this study, I estimate the impact of academic calendar systems on students' internship participation, using educational and employment histories from public LinkedIn profiles. Leveraging quasi-experimental variations in the timing of transitions from quarter to semester systems across institutions in Ohio, I find that semester systems increase students' internship participation by 16%. These additional internship experiences enhance students' labor market outcomes, increasing the likelihood that they secure non-entry-level positions with higher starting salaries after college.
Firm Pricing Strategy and Consumer Dishonesty: Evidence from the Bike-Sharing Industry (joint with Guangyu Cao, Wei Dai, and Juanjuan Meng)
This study examines the impact of firms' pricing policies on consumer dishonesty in the context of the sharing economy. We analyze over two million trip records from a bike-sharing company and develop measures of customers' dishonest behaviors at the trip level. Leveraging price variations from randomly distributed coupons and an exogenous price shock induced by a promotional campaign, we find that higher prices significantly increase the likelihood of dishonest behavior. Heterogeneity analysis reveals that this effect is more pronounced among male, non-student, and new users, as well as during nighttime hours. We also find suggestive evidence that the promotional campaign triggers reciprocal behavior from consumers, who demonstrate reduced dishonesty after experiencing the promotion, with prices held constant.
Family Spillover Effects of Marginal Diagnoses: The Case of ADHD (joint with Petra Persson and Maya Rossin-Slater)
American Economic Journal: Applied Economics, 17(2): 225-256, April 2025.
The health care system uses patient family medical history in many settings, and this practice is widely believed to improve the efficiency of health care allocation. This paper provides a counterpoint by documenting that reliance on hereditary information can amplify the misallocation of low-value care. We study Attention Deficit Hyperactivity Disorder, and show that reliance on family medical history generates a "snowball effect"—the propagation of an original marginal diagnosis to a patient's relatives. This snowball effect raises the private and social costs of low-value care.
Heuristics in Self-Evaluation: Evidence from the Centralized College Admission System in China (joint with Hongbin Li)
Forthcoming, the Review of Economics and Statistics
Using administrative data on the Chinese National College Entrance Examination, we study how left-digit bias affects college applications. We find strong discontinuities in students' admission outcomes at 10-point thresholds. Students with scores just below multiples of 10 make more conservative college application choices that place them into less selective colleges and majors. In contrast, students who score at or just above multiples of 10 aim and achieve higher but are at greater risk of overshooting. The discontinuity reveals that, despite the educational and labor market consequences, students' self-evaluation based on exam scores is subject to information processing heuristics.