We investigate how targeted groups react politically to racially motivated hate crimes within their communities. Combining incident-level administrative data on hate crimes in Los Angeles County from 2014 to 2022 with individual voter files, we exploit the hyperlocal variation in the geography and timing of these crimes. We find that serious anti-Hispanic hate crimes increase voter turnout among nearby Hispanics by 1.6 percentage points compared to nearby Whites. Communities with dense Hispanic populations and Hispanic advocacy and community service organizations are primarily responsible for this mobilization effect. Moreover, we demonstrate that hate crimes are associated with shifts in voters' policy preferences, particularly in the areas of crime prevention and affirmative action. Despite this, we do not find any significant differences in political participation among Black and Asian American communities following anti-Black and anti-Asian hate crimes, respectively. Los Angeles County's large Hispanic population and extensive network of community organizations may play an important role in fostering mobilization.

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.

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 from Louisiana local elections, U.S. state legislature elections, and Atlantic tropical storm names from 1980 to 2022, we find that down-ballot candidates experience an increase in vote share of 7.1–10.4 percentage points when a hurricane with the same name impacts the state prior to the election. This effect persists after accounting for the inherent popularity of specific names and potential strategic responses by candidates. Our result contributes to our understanding of political campaigning and advertising markets more generally.

This paper examines whether gender composition 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 does not affect males. The presence of males is a widely used cue for triggering stereotype threat in lab experiments, and additional evidence suggests our results are consistent with this concept: female students who are more inclined to endorse the math-gender stereotype are more strongly affected by gender composition. This study identifies a previously unexplored passive gender composition effect, providing new insights into the debate on education policy regarding single-sex versus mixed-sex schools.