We present the first large-scale empirical evidence on the effects of adopting a dynamic matching mechanism, in replacement of the Immediate Acceptance (IA) mechanism, on matching stability in college admissions in China. In 2007, the Inner Mongolia Autonomous Region introduced the "Real-time Dynamic Mechanism", which allowed college applicants to change their college choices as many times as they want during a restricted time interval while seeing their tentative admission outcome when they made each choice. Using administrative data on test scores and admission outcomes of the universe of National College Entrance Exam (NCEE) takers from 2005 to 2011, we construct measures of justified envy, an indicator of matching stability. We use a generalized difference-in-differences framework and, in contradiction to the theoretical and experimental predictions from previous studies, find no evidence that the real-time dynamic mechanism improved matching stability in the first four years after its implementation. Our findings suggest that the real-time dynamic mechanism is much less effective in eliminating justified envy than the parallel mechanism, a hybrid of IA and the Deferred Acceptance (DA) mechanism, which is now widely adopted in other provinces in China.

The past few years have seen a shift in many universities' admission policies from test-required to either test-optional or test-blind. This paper uses laboratory experiments to examine students' reporting behavior given their application package and the school's interpretation of non-reported standardized test scores. We find that voluntary disclosure is incomplete and selective, supporting both the incentive of partial unraveling (students with higher scores are more likely to report) and the incentive of reverse unraveling (students facing a better school's interpretation of non-reporting are less likely to report). Subjects exhibit some ability to learn about the hidden school interpretation, though their learning is imperfect. Using a structural model of student reporting behavior, we simulate the potential tradeoff between academic preparedness and diversity in a school's admission cohort. We find that, if students have perfect information about the school's interpretation of non-reporting,  test-blind is the worst and test-required is the best in both dimensions, while test-optional lies between the two extremes. When students do not have perfect information, some test-optional policies can generate more diversity than test-required, because some students with better observable attributes may underestimate the penalty on their non-reporting. This allows the school to admit more students that have worse observable attributes but report. The results are robust to a variety of extensions, including when schools have access to alternative signals of academic ability and standardized test score is a noisy but sufficiently informative measure of student ability.

This paper studies China’s nationwide ban on private academic tutoring for students in compulsory education and examines its effects on the supply of tutoring services, parental education investment, and distributional outcomes. First, using data collected from two major digital platforms, we document that 87.5 percent of private academic tutoring facilities exited the market following the ban. Then, using a novel nationally representative household panel survey on education expenditure, we compare students in compulsory education to high school students, who were not directly affected by the ban. We find that the ban led to a reduction in out-of-school tutoring spending but an increase in in-school education spending, resulting in an overall increase in total education expenditure. Moreover, middle-income households responded to the ban with lower education spending relative to both low- and high-income households, and students from these families reported worse academic performance. Further analysis suggests that households shifted away from tutoring institutions toward individual tutors and substituted large-group classes with more expensive one-on-one tutoring. These patterns point to reduced access to affordable tutoring options under the ban.