UC San Diego

Two chapters use same-sex marriage legalization to study couple formation. The third chapter, written jointly with Romaine Campbell, employs text analysis to study policing.Chapter 1. Policy can impact partner choice and match quality. Spousal visa policy permits non-residents to marry citizens. I ask how this policy affects couple rates, marriage rates, and assortative mating by citizenship and birth country. Without immigration policy variation, I identify the effect of spousal visa access by exploiting a change in the federal government's definition of spouse. When the Supreme Court ended the Defense of Marriage Act in United States v. Windsor, same-sex couples gained access to spousal visas for the first time. I estimate the effect of this policy change for mixed-citizenship same-sex couples, accounting for aggregate changes in other same-sex and mixed-citizenship couples, using a triple difference design. Spousal visa access causes a 36% increase in coupling rates and a 72% increase in marriage rates. Informal calculations suggest that 1.5 million people currently have partners, directly thanks to spousal visa policy. Chapter 2. Same-sex coupled men have the largest age gaps; different-sex couples have the smallest. Can differences in fertility expectations partially explain these differences? To answer this question, I estimate the relationship between age gaps and same-sex marriage legalization, which facilitates adoption and child-rearing. Using a stacked difference-in-differences design, I find that same-sex coupled women under 40 have smaller age gaps after marriage legalization compared to different-sex coupled women or older same-sex coupled women. There are no changes for men. Chapter 3. We ask if police officers' use of adjectives and adverbs systematically differs by suspect race, if officers with more race-predictive language have different 911 call dispatch outcomes, and if race-predictive language relates to other officer characteristics. We leverage a novel data set containing police report text. We identify race-predictive language using an elastic net with word counts, then construct an officer-level measure of race-predictive language. We find evidence that officers use different adjectives and adverbs in reports for Black versus White suspects. Our measure of such language correlates positively with officer inexperience and the number of use-of-force instances.