UC Santa Barbara

My dissertation consists of three chapters on discrimination, social media, and immigration, enriching the empirical literature of economic decision-making under risk and uncertainty.Chapter 1 explores the relative roles of beliefs and prejudice in the early weeks of the COVID-19 pandemic. Neither beliefs nor preferences are observed in most studies of discrimination, making it hard to discern the underlying motive. This study overcomes the challenge by testing two plausible motives in consumer discrimination following the first case of COVID-19. Did consumers avoid Chinese restaurants due to belief-based concerns over virus risks or due to anti-Chinese sentiment? Using foot-traffic data on the universe of US restaurants, I exploit variation in service type to capture perceived health risks and variation in the ethnic mix of customers to capture anti-Chinese sentiment. I find strong evidence consistent with belief-based discrimination and inconsistent with taste-based discrimination. Chapter 2 is closely related to Chapter 1 and examines the role of social media within the same observational setting. Specifically, this paper explores the role of social media in demand changes for restaurants following the first case of COVID-19. Using data on foot-traffic to the universe of US restaurants and Twitter data, I develop a novel identification strategy and exploit plausibly exogenous spatial variation in pre-covid Twitter usage to find that counties where Covid was a more salient topic of conversation on Twitter saw greater reduction in demand for Chinese restaurants relative to other restaurants. Placebo tests support the results, indicating a causal effect of social media on off-platform market choices. Chapter 3 studies the destination choices of asylum applicants. I use the destination choices of migrants who arrive under different statuses as a plausible counterfactual to estimate the effect of grant rates (recognition rates) on the share of applications for asylum received by a destination country. Using a relative discrete choice model, I find a robust estimate of a 6.5 percent increase in the share of applications received by destination countries in response to a 10 percentage point increase from the mean grant rate. This approach may provide applied researchers with a simple and convenient method to attain estimates in other settings.