We study the geographical allocation consequences of minimum wage, using individual-level migration data and the substantial variation over time in minimum wages across 262 counties in China. Our preferred specification shows that a 10% increase in the local minimum wage decreases the probability of outmigration by 1.52 percentage points. Using data from a major online recruitment platform, we further corroborate the main finding by showing that workers are less likely to search for a job in other cities when their city of residence experiences an increase in minimum wage. 

We study favoritism in the selection of elite scientific talent, by examining the relationship between host institution affiliation and performance in the Chinese Science Olympiad, where a gold medal guarantees a student's admission to top universities. Using hand-collected participant-level data (2003 - 2021), we find that students affiliated with the host province have a significantly higher winning probability, and the effect is more pronounced in host provinces where corruption norms are more prevalent. We further present evidence suggestive of cheating behavior using a portion of the contest vulnerable to information leakage, as well as the centralized post-Olympiad selection outside the control of host provinces. Together, our findings shed light on the crucial role of the organizational structure in designing equitable assessment systems for talent.

This paper examines whether gender composition in the workplace may influence cognitive performance in a real-world high-stakes setting. We use unique administrative data on students taking the college entrance examination in China, who are randomly assigned to test rooms with varying gender compositions. Our findings reveal that an increased presence of male students in the test room leads to a decreased performance of female students, but it doesn't influence males. This study identifies a previously unexplored passive gender composition effect and offers new perspectives on the debate over single-sex schools and mixed-sex schools.

I study whether voters' cognitive biases affect political candidates' entry decisions. Building off the insight that in down-ballot elections, voters tend to choose the first-listed candidate due to choice fatigue and the primacy effect, I conjecture that potential candidates with late-alphabet surnames, expecting positional disadvantages on an alphabetically ordered ballot, are less likely to run for office. Using within-state variation in ballot order rules and data on 341,156 candidates running for U.S. state legislatures from 1967 to 2022, I find that  alphabetically ordered ballots have an impact on candidate entry, resulting in a 3.68 percentage-point decrease in the representation of late-alphabet candidates (equivalent to a 16.4\% reduction). Moreover, alphabetically ordered ballots may unintentionally impact minority candidate entry, due to these candidates' distinctive distribution of surname initials.

We show that, in contrast to classic models of voting and political advertising, mere exposure to (and thus familiarity with) a candidate may lead to greater support. Using data on sub-national elections in Louisiana and names used for Atlantic tropical storms from 1982 to 2020, we find that a down-ballot candidate receives a 12.1-percentage-points higher vote share in elections where a same-name hurricane hit Louisiana before the election. This result holds after considering name-specific popularity and potential behavioral responses from candidates. Our result contributes to our understanding of political campaigning and advertising markets more generally.