Essays in Political Economics and Crime

Abstract

In this dissertation, I study three topics ranging from political economics to the economics of crime. In the first chapter, "Using Rain for Electoral Gain: Evidence from FEMA's Public Assistance Program", I study distortions in public spending---following large natural disasters---caused by elected officials at the state level in the United States (U.S.). I construct a novel county-level dataset that merges fine-grain physical measures of large destructive storms, satellite data on existing infrastructure, demographic information from Census, and administrative data that tracks multiple types of relief spending from several federal programs. To organize my empirical analysis I utilize a model of political competition between parties, that provides clear testable predictions. I find robust empirical evidence that political parties target public spending to counties with higher historic turnout relative to other counties within the same electoral district. To assuage fears that my results are driven by some unobserved bias or simply by chance, I propose two credible instrumental variables, explicitly model---and control for---the selection process that determines a counties eligibility for relief aid, and perform multiple placebo tests.

In the second chapter "It's Always Sunny in Politics"---co-authored with Carolina Concha-Arriagada---we study how election day weather impacts voter choice. Specifically we study an understudied dimension of weather---sunshine. Using novel daily weather measurements from satellites, linked to county-level U.S. Presidential electoral returns from 1948-2016, we document how sunshine affects the decision making of voters. We find that election-day exposure to sunshine increases support for the Democratic party on average. Additionally, we show that, contrary to prior findings that do not control for sunshine, precipitation has no detectable impact on partisan support, but universally depresses turnout. To rationalize our results we propose a mechanism whereby sunshine modulates voter mood which causes a change in voter choice, while precipitation only impacts turnout through increasing the cost of voting. We then build a theoretical model, which features this mechanism, and generates additional tests that we take to our data. Our results suggest that uninformative weather on election day, specifically sunshine, has detectable electoral impacts that teach us about voter choice.

In the third chapter, "Decomposing Racial Disparities in Incarceration: Evidence from a Southern U.S. Jurisdiction" I utilize high quality data developed from an almost two year relationship with a prosecutor's office located in a medium-sized jurisdiction in the southern United States. These data were carefully curated by a team of data scientists and engineers with institutional knowledge from prosecutors within the office. We first documents large raw racial disparities in incarceration and then decompose this raw disparity into systemic and direct components. We find that the systemic component vastly outweighs the direct component, implying that upstream racial differences drive the raw disparity.