The impact of ethnic diversity on the provision of local public goods and collective action in Africa remains largely unexplored. To address this gap, this paper explores the relationship between ethnic diversity and local primary school funding in rural western Kenya. The econometric identification strategy relies on the stable, historically determined patterns of ethnic land settlement in western Kenya. The main empirical result is that higher levels of local ethnic diversity is associated with sharply lower primary school funding and worse school facilities in western Kenya. The theory examines school choice and funding decisions when pupil mobility among schools is limited by land market imperfections and ethnic divisions, the relevant case for rural Africa, and predicts that local pupil transfers may lead to upward bias in OLS estimates of the impact of ethnic diversity. This theoretical prediction is confirmed in the data.

Most nations have experienced an internal armed conflict since 1960. The past decade has witnessed an explosion of research into the causes and consequences of civil wars, belatedly bringing the topic into the economics mainstream. This article critically reviews this interdisciplinary literature and charts productive paths forward. Formal theory has focused on a central puzzle: why do civil wars occur at all when, given the high costs of war, groups have every incentive to reach an agreement that avoids fighting? Explanations have focused on information asymmetries and the inability to sign binding contracts in the absence of the rule of law. Economic theory has made less progress, however, on the thornier (but equally important) problems of why armed groups form and cohere, and why individuals decide to fight. Likewise, the actual behavior of armed organizations and their leaders is poorly understood. On the empirical side, a vast cross-country econometric literature has aimed to identify the causes of civil war. While most work is plagued by econometric identification problems, low per capita incomes, slow economic growth and geographic conditions favoring insurgency are the factors most robustly linked to civil war. We argue that micro-level analysis and data are needed to truly decipher war’s causes, and understand the recruitment, organization, and conduct of armed groups. Recent advances in this area are highlighted. Finally, turning to the economic legacies of war, we frame the literature in terms of neoclassical economic growth theory. Emerging stylized facts include the ability of some economies to experience rapid macroeconomic recoveries, while certain human capital impacts appear more persistent. Yet econometric identification has not been adequately addressed, and there is little consensus on the most effective policies to avert conflicts or promote postwar recovery. The evidence is weakest where it is arguably most important: in understanding civil wars’ effects on institutions, technology, and social norms.

This Dissertation consists of three empirical applications on the economics of crime and law enforcement.

Chapter 1 uses over 200,000 patrol stops conducted by the Oakland Police Department to estimate differences in policing behavior among black, white, Hispanic, and Asian officers. In contrast to previous studies which consider average differences at the city or state level, this study uses individual officers' patrol assignments and the exact date, time, and geographic coordinates of each stop to identify between-officer differences.

The data indicate little to no differences across officer race on average, but substantial differences within neighborhoods. In general, minority officers less intensely police all races in minority neighborhoods, but more intensely police all races in white neighborhoods relative to their white officer peers.

A model of police behavior with imperfect information offers one explanation for this result. In the model, an unbiased officer with relatively high ability to interpret suspect behavior polices with relatively low intensity. The observed outcomes are then consistent with officers possessing neighborhood-specific informational advantages in policing, particularly with respect to their own race. That is, minority officers better interpret suspect behavior in minority neighborhoods, while white officers better interpret suspect behavior in white neighborhoods. Simulation results suggest that small differences in interpretative ability (modeled as noise in signals observed by the officer) can generate the observed magnitudes.

Chapter 2, which is coauthored with Justin McCrary, presents evidence from six data sets on the participation of youth in crime near the age of criminal majority. The evidence suggests smooth behavior through the transition to adulthood, despite substantial changes in punitiveness, and is consistent with small deterrence effects of long prisons sentences for young offenders.

Chapter 3 reconsiders the empirical analysis of Knowles, Persico, and Todd (2001). Knowles, Persico, and Todd (2001) presents a model of police and motorist behavior in the context of vehicle searches, and tests it using data from Maryland. The main implication of the Knowles et al. model is that in the absence of racial discrimination, the proportion of searches yielding drugs (or ''hit rate'') will be equated across races. A relatively low hit rate for any group suggests that police may improve their overall hit rate by shifting resources away from that group, and is thus evidence toward discrimination. Using data on vehicle searches by Maryland State Police, they find no bias against blacks relative to whites, but significant bias against white females and particularly Hispanics.

However, while their study focused on searches occurring along Interstate 95, this study considers all vehicle searches in Maryland, both for the time period studied in Knowles, Persico, and Todd (2001) (1995--1999) and in more recent years (1995--2006). The main results suggest substantially lower hit rates for blacks for searches occurring off Interstate 95, though almost no difference for searches on Interstate 95.

The first chapter of my dissertation studies the 2011 student movement in Chile, the largest protest mobilization in the country's history, in which hundreds of thousands of students skipped school to protest with the goal of reforming the educational system. Using administrative data on millions of students' daily school attendance decisions on protest and non-protest days, a large network composed by the lifetime history of classmates, and differential network exposure to the first national protest, I employ an instrumental variables approach to test how networks affect protest behavior. The main finding is that individual participation follows a threshold model of collective behavior: students were influenced by their networks to skip school on protest days only when more than 40 percent of the members of their networks also skipped school. Additional findings show that protest participation imposed significant educational costs on students and helped to shift votes towards non-traditional opposition parties. Taken together, results indicate that networks amplify the effect of protests in non-linear ways with potentially significant consequences for institutional change.

The second chapter, co-authored with Jose Ignacio Cuesta and Cristi'an Larroulet, investigates the workings of educational institutions in Chile. In education, data on school quality is often gathered through standardized testing. However, the use of these tests has been controversial because of behavioral responses that could distort performance measures. We study the Chilean educational market and document that low-performing students are underrepresented in test days, generating distortions in school quality information. These distorted quality signals affect parents' school choice and induce misallocation of public programs. These results indicate that undesirable responses to test-based accountability systems may impose significant costs on educational markets.

The third chapter, co-authored with Mounu Prem, studies firms during Chile's transition to democracy. Political transitions are associated with significant economic changes, but little is known about how firms fare across regimes. We study Chile's democratization and show that firms in the dictator's network make critical investments in physical capital during the political transition. These investments are made possible by government banks during the dictatorship and allow firms to improve their market position in the new regime. Our results show how market distortions can be transferred across political regimes.

AIDS deaths could have a major impact on economic development by affecting the human capital accumulation of the next generation. We estimate the impact of parent death on primary school participation using an unusual five-year panel data set of over 20,000 Kenyan children. There is a substantial decrease in school participation following a parent death, and a smaller drop before the death (presumably due to pre-death morbidity). Estimated impacts are smaller in specifications without individual fixed effects, suggesting that estimates based on cross-sectional data are biased toward zero. Effects are largest for children whose mothers died, and those with low baseline academic performance.