Browsing by Subject "Labor economics"

How households and individuals respond to adverse and unanticipated shocks is an important concern for both economists and policy makers. This is especially true in developing countries where poverty, weak infrastructure, and a lack of social safety nets often exacerbate the effects of adverse shocks on household welfare. My research addresses these issues in the context of three economic outcomes and behaviors - early life health and the accumulation of human capital, willingness to take on financial risk, and behavior in the labor market. The results of this research project both adds to our understanding of how life experiences shape individuals' well-being and behavior and how policy can help individuals achieve long-term improvements in the lives following adverse events.

My research focuses on households and individuals affected by a large-scale natural disaster, the 2004 Indian Ocean tsunami. I utilize data from the Study of the Tsunami Aftermath and Recovery (STAR), a unique longitudinal survey of individuals and households living in coastal communities in Aceh and North Sumatra, Indonesia, at the time of the tsunami. The STAR surveys were conducted annually for five years after the disaster and include a wide range of demographic, economic, and health measures.

In the first chapter, Child Height after a Natural Disaster, co-authored with Elizabeth Frankenberg, Duncan Thomas, and Jed Friedman, we investigate the immediate and long-run impacts on child health of in utero exposure to stress induced by the tsunami. We investigate whether in utero exposure to stress, as measured by tsunami-induced maternal posttraumatic stress, affected the growth of children born in the aftermath of the tsunami in the critical first five years of their lives. Although previous studies suggest that in utero exposure to stress is related to a number of adverse birth outcomes such as prematurity and lower birth weight, there is little evidence of the impact on linear growth, a strong correlate of later life income. We find evidence that children exposed to high levels of stress beginning in the second trimester experienced reduced growth in the first two years of their lives. We also find evidence that growth reductions largely disappear by age five. This suggests that significant catch-up growth is possible, particularly in the context of pronounced post-disaster reconstruction and economic rehabilitation.

In the second chapter, The Impact of a Natural Disaster on Observed Risk Aversion, I investigate the short and long-term impacts of the 2004 Indian Ocean tsunami on attitudes toward risk. Attitudes toward risk are important determinants of economic, demographic, and health-related behaviors, but how these attitudes evolve after an event like a natural disaster remains unclear because past research has been confounded by issues of selective exposure, mortality, and migration. My study is the first to directly address these problems by utilizing exogenous variation in exposure to a disruptive event in a sample of individuals that is representative of the population as it existed at the time of the event. In addition, intensive efforts were made to track migrants in the sample population, which is important for this study because migration is common following events like natural disasters and is likely related to attitudes toward risk. I find that physical exposure to the tsunami (e.g., seeing or hearing the tsunami or being caught up in the tsunami) causes significant short-term decreases in observed aversion to risk, especially for the poor, but few longer-term differences. This finding has important implications for the design of effective post-disaster assistance policies. In particular, it implies that post-disaster assistance programs should include aid that is consistent with the observed risk attitudes of the survivors such as job training and capital to start-up businesses.

In the last chapter, Labor Market Outcomes following the 2004 Indian Ocean Tsunami, I investigate how labor market outcomes changed in coastal communities in Aceh and North Sumatra following the tsunami and the post-disaster recovery efforts. Although restoring the livelihoods of survivors of adverse events is critical for their long-term recovery, there is little evidence from developing countries of how labor market outcomes change after such events. Using the STAR data, I find a significant and persistent increase in paid employment for younger women in urban communities. The increase occurred in communities that were heavily damaged by the tsunami and those that were not, suggesting that the impacts of the disaster on livelihoods are likely long-lasting and extend beyond the communities that were directly stuck by the disaster.

This dissertation consists of three separate essays that use dynamic models to better understand the human capital accumulation process. First, I analyze the role of migration in human capital accumulation and how migration varies over the business cycle. An interesting trend in the data is that, over the period of the Great Recession, overall migration rates in the US remained close to their respective long-term trends. However, migration evolved differently by employment status: unemployed workers were more likely to migrate during the recession and employed workers less likely. To isolate mechanisms explaining this divergence, I estimate a dynamic, non-stationary search model of migration using a national longitudinal survey from 2004-2013. I focus on the role of employment frictions on migration decisions in addition to other explanations in the literature. My results show that a divergence in job offer and job destruction rates caused differing migration incentives by employment status. I also find that migration rates were muted because of the national scope of the Great Recession. Model simulations show that spatial unemployment insurance in the form of a moving subsidy can help workers move to more favorable markets.

In the second essay, my coauthors and I explore the role of information frictions in the acquisition of human capital. Specifically, we investigate the determinants of college attrition in a setting where individuals have imperfect information about their schooling ability and labor market productivity. We estimate a dynamic structural model of schooling and work decisions, where high school graduates choose a bundle of education and work combinations. We take into account the heterogeneity in schooling investments by distinguishing between two- and four-year colleges and graduate school, as well as science and non-science majors for four-year colleges. Individuals may also choose whether to work full-time, part-time, or not at all. A key feature of our approach is to account for correlated learning through college grades and wages, thus implying that individuals may leave or re-enter college as a result of the arrival of new information on their ability and/or productivity. We use our results to quantify the importance of informational frictions in explaining the observed school-to-work transitions and to examine sorting patterns.

In the third essay, my coauthors and I investigate the evolution over the last two decades in the wage returns to schooling and early work experience.

Using data from the 1979 and 1997 panels of the National Longitudinal Survey of Youth, we isolate changes in skill prices from changes in composition by estimating a dynamic model of schooling and work decisions. Importantly, this allows us to account for the endogenous nature of the changes in educational and accumulated work experience over this time period. We find an increase over this period in the returns to working in high school, but a decrease in the returns to working while in college. We also find an increase in the incidence of working in college, but that any detrimental impact of in-college work experience is offset by changes in other observable characteristics. Overall, our decomposition of the evolution in skill premia suggests that both price and composition effects play an important role. The role of unobserved ability is also important.

My dissertation examines human capital investments and their role in individual's labor market outcomes. Chapter 2 analyzes how public school teachers decide to make human capital investments and the effects that these decisions have on their future labor market outcomes. In particular, I look at the decisions of employed teachers to obtain an advanced degree. Teachers' education and career decisions are modeled via a dynamic framework in the presence of teacher-specific unobserved heterogeneity. I find that teachers' decisions to obtain master's degrees are motivated by more than just an increase in salary. In particular, I observe teachers with master's degrees receiving a better draw on job characteristics, as measured by school quality, and that teachers are willing to pay between $1,500 and $20,000 to to move up one quartile in school quality. I also find that teachers value having broad access to online degree programs more than they dislike tuition costs. Counterfactual simulations by unobserved ability are consistent with a story that high-type teachers value both the salary increase and a better draw in career prospects, whereas low-type teachers are mostly interested in the salary increase.

Chapter 3 investigates the evolution over the last two decades in the wage returns to schooling and early work experience. Using data from the 1979 and 1997 panels of the National Longitudinal Survey of Youth, we isolate changes in skill prices from changes in composition by estimating a dynamic model of schooling and work decisions. Importantly, this allows us to account for the endogenous nature of the changes in educational and accumulated work experience over this time period. We find an increase over this period in the returns to working in high school, but a decrease in the returns to working while in college. We also find an increase in the incidence of working in college, but that any detrimental impact of in-college work experience is offset by changes in other observable characteristics. Overall, our decomposition of the evolution in skill premia suggests that both price and composition effects play an important role. The role of unobserved ability is also important.

In this dissertation I study the long-term effects of post-disaster reconstruction of infrastructure on economic and demographic outcomes. The effects on individuals and communities that result from shocks to existing infrastructure have not been widely explored in the economic and development literature. As some of the largest natural disasters in recent times have shown, massive destruction of infrastructure is followed by large influxes of resources aimed at the reconstruction of damaged property. For example, after the 2004 Indian Ocean tsunami, Indonesia alone received enough aid to deal with the estimated seven billion dollars in infrastructure losses. While there are studies that address how money was allocated, there is hardly any good empirical evidence that provides a causal estimate of the effect that large reconstruction programs have on targeted beneficiaries. In this dissertation I address this gap in the literature.

The context of my study is the 2004 Indian Ocean tsunami, one of the most devastating natural disasters in recent years. In particular, the location for this analysis is the Indonesian province of Aceh, which was the area hardest hit by the disaster (Chapter 2). One of the main reasons why long-term impacts of post-disaster reconstruction remain an understudied topic is the lack of access to data that tracks individuals over time and across space. Having longitudinal data of this type provides a more complete picture of beneficiaries of post-disaster aid, as well as the effects of reconstruction programs on economic outcomes and demographic processes, such as migration. My dissertation addresses this concern by using a unique, population representative panel of survivors of the Indian Ocean tsunami, the Study of the Tsunami Aftermath and Recovery (STAR), which collected extensive individual, household, and community data in Aceh, Indonesia, every year between 2005 and 2010, with an additional follow-up in 2015 (Chapter 3).

Using these data, the first question I explore empirically is an estimation of the causal effects of reconstruction of the housing stock on a multidimensional set of well-being measures (Chapter 4). First, I show that post-tsunami reconstruction was largely determined by the level of damage, regardless of pre-tsunami characteristics of communities, households, and individuals. Based on this finding, I identify the causal effects of housing reconstruction on post-disaster well-being using an individual fixed effects strategy. I show that housing reconstruction causes significant reductions in levels of post-traumatic stress reactivity, and significant increases in socioeconomic well-being. These effects are mainly concentrated after two years of housing tenure, and among those from highly damaged communities. Housing reconstruction has a positive relationship with self-rated physical health (although these estimates are not statistically significant). These results provide important causal evidence of how reconstruction of infrastructure after a natural disaster can have long-lasting, positive consequences for the recovery of survivors.

Next, I continue looking at the effects of rebuilding individual assets (i.e. the home) but turn to the analysis of migration, a key demographic process following natural disasters. Specifically, I look at migration and its relationship with housing reconstruction and well-being (Chapter 5). The 2004 Indian Ocean tsunami displaced large numbers of people. In Aceh, Indonesia, an estimated 500,000 people left their communities after the disaster. In this research, we provide a demographic perspective on displacement and longer-term adaptation and recovery after a disaster. We describe patterns of mobility among tsunami survivors, including those who did not return to their origin communities, those who did return, and those who never left. We also consider mobility among those living in communities that did not suffer tsunami damage. We then examine how the likelihood of receiving housing aid varies across these subgroups. Finally, we consider how measures of subjective well-being evolve after the disaster. Results show that predictors of relocation vary significantly across individuals depending on the level of exposure of communities to the physical damage of the tsunami. Relocation decisions, and in particular staying in the pre-tsunami community, are highly related to the likelihood of benefiting from housing aid. And, changes in subjective well-being not only depend on receipt of housing aid but also on interactions between relocation decisions.

The last empirical analysis changes the focus from the reconstruction of individual assets to the reconstruction of community infrastructure (Chapter 6}), an important component of post-disaster rebuilding programs. In the aftermath of the tsunami, it is estimated that a total of 2,600 km of roads and 119 bridges needed rebuilding. In less than four years a total of 3,700 km of roads and all the destroyed (or damaged) bridges had been rebuilt \citep{indonesia2010provincial}. Roads can be an important gateway to economic development, so in this analysis I focus on estimating the economic effects of road reconstruction in post-tsunami Aceh. First, I exploit variation in timing of road reconstruction projects at the community level and, using a fixed effects strategy, I show that road reconstruction may not be enough to cause significant economic effects, but that quality of road construction matters, specifically access to all-weather roads. Further, I also show that road reconstruction that happens in combination with public works programs has additional positive effects. I provide further evidence on the effects of road reconstruction by looking at the specific case of the reconstruction of the Banda Aceh-Meulaboh road. The Banda Aceh-Meulaboh road is a good example of a project that seeks to restore large public infrastructure after a major shock to the built environment under the assumption that it would contribute to restore economic activity in the area. Using a difference-in-differences strategy, I exploit changes in access to the road between 2005 and 2015. I show that gaining access to the road has positive and modest effects both on individuals and households and, in particular, on households in rural areas. I did not find any statistically significant negative effects of losing access to the road but results from this case study point that losing access may be hindering some progress, for example, to translate work opportunities into higher wages.

Taken together, results from the empirical analyses in this dissertation fill an important gap in our understanding of what happens to disaster victims in the long-run, how they benefit from reconstruction programs that rebuild both individual and community assets, and how these programs can have long-lasting consequences on economics and demographic trajectories of populations. As a result, my study not only represents an important contribution to existing literature, but it also underscores the importance of having data collection projects that account for the long-term nature of infrastructure reconstruction projects. Natural disasters are projected to become increasingly more common, and this type of data can result in empirical research, like this dissertation, that can improve our understanding of how disaster victims cope, which strategies work best and why, and create lessons that can inform disaster management and reconstruction policies that will result in successful post-disaster experiences.

This dissertation considers the role gender plays in labor markets, household decision-making, and health in sub-Saharan Africa.

The first chapter considers the impact of fast Internet access on employment outcomes and household dynamics. I find the introduction of fast Internet to sub-Saharan Africa significantly increased employment for males, but had little impact on female employment. In addition, it significantly increased perceived acceptability, among both genders, of domestic violence against women.

The second chapter considers the differential impact, by gender, of an experimental labor market intervention in South Africa, which measured skills of workseekers and provided a mechanism for workseekers to communicate their results to potential employers. I find that men experienced a larger effect of the intervention on employment outcomes than did women. This difference is largely explained by pre-existing differences between genders, rather than differential responses to treatment.

The third chapter considers the factors that contribute to female genital cutting (FGC) in Mali and tests various hypotheses to explain the persistence of the tradition. I find that maternal preference is pivotal in the decision to cut daughters. I also find that the marriage market hypothesis and the identity hypothesis of FGC decision-making are alone insufficient to explain persistence.

This dissertation presents three essays on topics in development economics. Drawing on rich longitudinal data as well as measures of cognitive skills adapted from cognitive neuroscience, the chapters focus on health and human capital through the life course. The first essay isolates the causal impact of public health insurance on child health, measured by height-for-age, by exploiting the roll-out of Seguro Popular, a large-scale program that provides public health insurance to about half of Mexico’s population. Drawing on insights from the biology of human linear growth and using population-representative longitudinal data, we establish that Seguro Popular has had a modest impact on child nutritional status. These effects were larger after the program had been established for several years, suggesting that supply-side factors may have been critical impediments. The second essay turns to the relationship between executive function and labor market outcomes. This project describes how a widely used measure of executive function with foundations in cognitive neuroscience was implemented as part of a large-scale, population-representative survey in Indonesia. I find that higher cognitive functioning is associated with rewards in the labor market, particularly for women, and that executive function is related to labor force participation and the choice between wage work and self-employment. Motivated by the importance of executive function and human capital in later life, the third essay turns to the relationship between parental executive functioning and child outcomes. I find that parental executive function is strongly related to child executive function, and that better parental executive function is associated with better child nutritional outcomes, as measured by height-for-age and weight-for-height. The relationship between parents’ executive functioning and child outcomes depends both on the gender of the child and whether the child is first born or has older siblings. These results suggest that the relationships I observe between parental executive functioning and child development are not simply genetic but reflect parental choices and behaviors. Together, these chapters demonstrate the importance of bringing the tools from cognitive neuroscience to economics to further examine the role that specific cognitive skills like executive function play for success and well-being. They also highlight the critical importance of the early childhood household and environment for development, with long-lasting consequences for later life.

This dissertation consists of three separate essays on the economics of education. In the first chapter, co-authored with Esteban Aucejo, studies the relative effectiveness of reducing absences to extending the school calendar on test score performance. Using administrative data for North Carolina public schools, we exploit a state policy that provides variation in the number of days prior to standardized testing and find substantially larger effects for absences relative to additional days of class.

The second chapter, co-authored with Esteban Aucejo, analyzes whether different institutional settings could affect how school administrators and teachers respond to possible extensions of the school calendar. We present a theoretical model in which principals set the date of the test and teachers decide how much effort to exert in the classroom with and without monetary performance bonuses for teachers. Leveraging the removal of monetary bonuses during the sample period, we utilize a difference-in- difference estimation strategy and find that, consistent with the theoretical model, low performing schools are more likely to make extensive use of the testing window when monetary bonuses are in place; this behavior disappears after changes to the scheme of incentives.

In the third chapter, I present joint work with Peter Arcidiacono, V. Joseph Hotz and Arnaud Maurel, utilizing data on subjective expectations of outcomes from counterfactual choices to recover ex ante<\italic> treatment effects as well as the non-pecuniary benefits associated with different treatments. The particular treatments we consider are the choice of occupation. By asking individuals about potential earnings associated with counterfactual choices of college majors and occupations, we can recover the full distribution of ex ante<\italic> monetary returns to particular occupations, and how they vary across majors. We then link subjective expectations to a model of occupational choice, enabling the examination of how individuals tradeoff their preferences for particular occupations with the corresponding monetary rewards. While sorting across occupations is partly driven by the ex ante<\italic> monetary returns, sizable differences in expected earnings across occupations remain after controlling for selection on monetary returns, which points to the existence of substantial compensating differentials.

This dissertation consists of two related essays on the economics of immigration. The first chapter presents new evidence on whether the earnings of foreign-born workers grow faster than that of similarly educated natives. We compare cross-sectional and panel analyses of assimilation in the U.S. context. The panel data allow us to control for fixed unobserved heterogeneity in earnings. As others have found for earlier entry cohorts, we find that immigrants with less than a college education start at an earnings disadvantage but converge toward native earnings with time in the U.S. in the cross-section. Lower earning immigrants selectively leave on-the-books jobs. We also find substantial selection among low earnings natives who also tend to work less and leave the labor force earlier. Both groups display selection and the net result is that controlling for fixed unobserved heterogeneity has little effect on the relative earnings growth of low-skilled immigrants.

We find very different results for high-skilled workers. In the cross-sectional analysis, immigrants whose highest level of education is a bachelor's degree exhibit a decline in relative earnings with time in the U.S. However, for these immigrants, the inclusion of an individual fixed effect reveals faster earnings growth relative to natives. Among both immigrants and natives, lower earners selectively leave the covered sector. However, because low earning immigrants who remain in the sample become more likely to work with time in the U.S., the net result is that the average earnings of immigrants diminish. These results indicate that controlling for individual heterogeneity is important in estimating the economic assimilation of immigrants.

The second chapter examines the role of the workplace in earnings assimilation. Using an earnings panel much like in the first chapter, we consider whether job characteristics such as firm size, industry, and firm specific tenure can account for earnings differences between native and foreign-born workers. We focus on workers with less than a college education and find that the job characteristics considered account for almost all of the faster earnings growth of high school dropouts and half of the faster earnings growth of high school graduate immigrants. Rising relative job tenure of immigrants is the most important factor.

Social norms can play an important role in economic decision-making. Individuals face costs if they deviate from cultural norms in their families or communities, and firms seek to preserve reputation in order to bolster their position in their market. In this dissertation, I explore the role of cultural norms and reputation in individual, household, and firm decision-making in developing countries. The first chapter is comprised of information and priming experiments on a job search platform in urban Pakistan identifying the role of social norms and workplace attributes on educated women's job search and occupational choice. The second chapter studies the relationship between gold price in year of birth and household decision-making at adulthood using nationally representative data in India. The third chapter combines a lab-in-field generosity game with field-based measures of healthcare provider effort to document that a sizable proportion of healthcare providers in this setting in rural India exert clinical effort with patients in ways consistent with maintaining reputation in their communities.

This dissertation considers how families affect economic decisions across two different settings. In Chapters 2 and 3, I use data from Indonesia to understand the role that flexibility plays in job choice for women and how it interacts with children. These chapters take different approaches to the same broad set of questions. In Chapter 2 I ask whether the cost of temporal flexibility varies between wage employment and self-employment, especially for mothers. I find all women are willing to give up a portion of their wage rate to work fewer hours and have more flexible hours. However, the cost to women of fewer hours and more flexible hours varies by whether a woman is self-employed or wage employed and whether she has children. All self-employed women and wage-working mothers are willing to give up more than 10% of their wages for a 10% increase in flexibility but the trade-off is steeper for mothers in wage employment than in self-employment. In Chapter 3, I use qualitative in-depth interviews to better understand the nuances that go into work decisions for both women and men and how these choices affect and are affected by their children. This study echoes the first in that women often discussed the importance of flexibility in their work arrangements, in particular to their choices in self-employment. These findings have implications for policies and programs designed to foster entrepreneurship in developing countries. Chapter 4 asks questions about how parents provide for children- albeit in a very different context. Using panel data from the United States, the paper examines the influence of parental wealth and income on children's college attendance and parental financing decisions, graduation, and quality of college attended, and whether parental financing affects the subsequent indebtedness of parents and children. Higher levels of parents' wealth and income increase the likelihood that children attend college with financial support relative to not attending college, and that parental wealth increases the likelihood that children graduate from college. We show descriptive evidence that parental support for college increases the subsequent level of housing debt that parents hold but does not reduce student debt for children.

This dissertation is a collection of three chapters all pertaining to institutional economics. In short, the eld of institutional economics is an outgrowth of public economics, in the sense that in many cases he key institutions that frame economic decisionmaking are the product of public policy. However this is not exclusive. Institutional economics' key contribution is the acknowledgement that cultural and social institutions --- often developed organically over the course of centuries --- can play as signicant a role in individuals' economic choices as governmental policy. In the pages that follow, we will address the economic impact of cultural and political institutions in three contexts: Judicial decisionmaking in Islamic courts, the effects

of negative health shocks on retirement savings, and the tradeoff between retirement savings and investment in durable goods.

This dissertation explores three aspects of job mobility in three essays.

The first essay, "Job Mobility Within and Across Occupations," assesses the impact of occupational mobility on life cycle wage inequality. I develop a model of job mobility which attributes differential returns to occupations to occupationally heterogeneous labor market frictions, compensating differentials, and non-pecuniary job switching costs. I estimate the structural model on linked Hungarian administrative data and use it to quantify the relative importance of each of these mechanisms. High-skill occupations offer higher wages and more stable employment; in turn, low-skill occupations feature higher non-wage amenities but larger non-pecuniary costs of switching to high-skill jobs. As a result, workers who start their careers in the bottom 10 percent of the wage distribution in a high-skill occupation surpass those who start in the top 5 percent of a low-skill occupation in 5 years. I find that occupationally heterogeneous labor market frictions are the key drivers of these ex ante wage profiles. These results indicate that occupational heterogeneity in the sources of wage inequality is instrumental to fully account for life cycle wage dynamics.

The second essay, "Conditional Choice Probability Estimation of Continuous-Time Job Search Models," introduces a novel framework to analyze mobility across jobs and out of unemployment. My coauthors and I adapt the conditional choice probability estimation method to a continuous-time job search environment. To do so, the proposed framework incorporates preference shocks into the canonical job search model, resulting in a tight connection between value functions and conditional choice probabilities. Our method, relative to standard estimation methods for continuous-time job search models, yields considerable computational gains. In particular, this method makes it possible to estimate rich, possibly non-stationary, job search models without having to solve any differential equations, and in some cases even avoiding optimization altogether. We apply our method to analyze the effect of unemployment benefit expiration on the duration of unemployment and wages using rich longitudinal data from Hungarian administrative records.

The third essay, "Coworker Networks and the Role of Occupations in Job Finding," asks which former coworkers help displaced workers find jobs. My coauthor and I answer this question by studying occupational similarity in job finding networks. Using matched employer-employee data from Hungary, this paper relates the unemployment duration of displaced workers to the employment rate of their former coworker networks. Overall, while coworkers from all occupations are helpful in job finding, we find significant heterogeneity by occupation skill-level. For workers in low-skill jobs, coworkers who worked in the same narrow occupation as the displaced worker are the most useful network contacts. For workers in high-skill jobs, coworkers from different occupations are the most useful network contacts.

Skills are central to many questions in labor economics ranging from the causes of rising wage inequality to understanding how individuals make decisions about their career. However, skills are typically measured incompletely in standard datasets, so an important empirical challenge in labor economics is to develop methods to measure or control for these unobserved variables. This dissertation builds a range of methodologies to deal with unobserved skills in models in labor economics and explores how the evolution of workers' skills has contributed to long-term trends in wage inequality.

Chapter 2 develops an approach to estimating workers’ skills from panel data and examines how changes in skills and occupational sorting patterns have contributed to rising wage inequality in the United States since the 1980s. The methodology uses repeated measurements of individuals’ labor market outcomes over time to reveal their underlying skills. Estimating a model of occupational choice using panel data from the Survey of Income and Program Participation (SIPP), I find that (1) as tasks in high-skill jobs have become increasingly complex, the distribution of workers' ability to perform those tasks has become more dispersed, (2) workers' ability to perform low-skill work tasks has become more homogeneous, and (3) workers have increasingly sorted into occupations by skill level, which has increased wage inequality.

Chapter 3 builds a related panel data methodology that can accommodate a more general class of models in which individuals can have imperfect information about their abilities. In particular, in addition to unobserved heterogeneity known to individuals, the methodology in this chapter also allows for initially unpredictable heterogeneity that may be revealed over time.

Chapter 4 develops a complementary approach to assessing the sensitivity of estimates of causal effects to omitted variable bias. In the canonical example of omitted variable bias, the presence of unobserved ability creates a bias in estimates of the causal effect of education on wages. This chapter provides an approach to quantifying the size of this bias by reasoning about the importance of unobserved ability compared to other included variables. In contrast to existing methods for sensitivity analysis in this setting, the approach also allows the research to explicitly reason about correlation between the omitted variable and observed controls.

The essays in this dissertation explore how barriers to advancement may lead to path dependence in economic outcomes. One uses a finite mixture model to demonstrate that some police officers are more likely than others to stop African-American drivers. The conclusion is one that though widely believed has proven challenging to establish empirically. By doing so, the analysis makes two contributions. First, it more closely aligns with the understanding of racial profiling. While disproportional susceptibility to vehicle searches exemplifies profiling, being pulled over is a much more common margin for police interaction, which this paper models a tractable way of identifying. Second, studies of secondary decisions such as searches frequently assume that there is no bias in the initial stop decision. An analysis of traffic stops across eight states questions this assumption, concluding that stopped drivers constitute a selected sample. Although bias is theoretically continuous, average behavior fits well into two distinct groups, with 30–40% of officers in the group that exhibits a relatively high propensity to stop minority drivers. The implication is that race-based policing is more prevalent than the "rotten apples" theory might suggest. The second essay asks how job loss is distributed in an unexpected downturn, examines the equity consequences, and evaluates policy responses. After demonstrating two novel empirical patterns relating job loss risk to earnings, it constructs and estimates a search model with heterogeneous job termination rates to explain the prevailing dynamics, and then uses it to evaluate the impact of large-scale transfers, unemployment insurance, and an earnings subsidy during a simulated downturn. Transfers have a minimal employment effect unless the shock also reduces savings. Raising unemployment benefits by 30% leads to a 0.6 point increase in the unemployment rate. Adding an earnings subsidy to unemployment benefits raises employment by 7 percentage points at a 23% lower level of inequality yet increases costs by only 16-30%. The tradeoff is lower employment at better paying jobs versus higher consumption at subsidized low-wage jobs. In contrast to a compensating differentials framework, the model shows that lower earners tend to be more at risk for layoffs, and that this effect is stronger following a negative aggregate shock. Following a simulated shock, mean consumption falls by 5% yet consumption at the 10th percentile drops by 16%.

This dissertation studies three questions in labor economics centering around immigration policy and its effects on vulnerable populations. I use administrative data from the United States (U.S.) and Germany to address these questions empirically.

In the first chapter, I investigate the effects of an increase in immigration enforcement through local police force on domestic violence victims’ help-seeking behavior. I use a fixed effects model, a generalized synthetic control method and novel administrative data on the use of services for domestic violence victims in North Carolina. In North Carolina, a large fraction of individuals of Hispanic origin are undocumented immigrants or connected to undocumented immigrants. I find that local immigration enforcement significantly reduces Hispanics’ use of domestic violence services. It does not affect service use by African Americans who are predominantly U.S.-born citizens. This suggests that the decrease in Hispanics' service use is directly related to their immigration status and not driven by a general effect on minorities. I do not find any robust evidence that local immigration enforcement affects intimate partner homicides of Hispanic women.

The second chapter studies the relationship between workforce demographics, workplace hazard, and worker complaints about hazardous or illegal working conditions. In joint work with Matthew Johnson, I examine if worker complaints are effective in directing inspections by the U.S. Occupational Safety and Health Administration to the most hazardous workplaces. We measure worker complaints and workplace injuries by inspections triggered by a worker complaint and a serious workplace injury, respectively. We find that the complaint rate in a county and industry is positively associated with its recent injury rate. This relationship changes for workplaces with a high share of Hispanic workers. Workplaces that employ larger shares of Hispanic workers have lower complaint rates, but higher injury rates. We use fixed effects regressions to estimate the effect of local immigration enforcement on Hispanic workers' willingness to complain about hazardous conditions. We find that stronger enforcement significantly reduces worker complaints, but not workplace injuries in workplaces with a high share of Hispanic workers. This provides evidence that stronger local immigration enforcement reduces Hispanic workers' willingness to complain about unsafe working conditions irrespective of the true workplace hazard.

In the third chapter, I investigate the effect of integrating refugee students in elementary schools on the academic performance of native students. Using administrative data from Germany, I exploit the variation in the percentage of refugee students within schools to account for endogenous sorting of refugees into schools. I do not find any evidence for negative effects of refugee students' integration on the academic performance of native elementary students. In contrast, exposure to refugee students reduces mandatory grade retention rates of German fourth graders. Effects on the percentage of students who receive a recommendation for the higher secondary track are very small and statistically insignificant. I also show that refugee students attend schools where German students' performance is lower.

This dissertation is comprised of three essays in the economics of education. In the first essay, I examine how college students' major choice and major switching behavior responds to major-specific labor market shocks. The second essay explores the incidence and persistence of overeducation for workers in the United States. The final essay examines the role that students' cognitive and non-cognitive skills play in their transition from secondary to postsecondary education, and how the effect of these skills are moderated by race, gender, and socioeconomic status.

This dissertation consists of three essays on the topic of education policy. In the first essay, I evaluate the impacts of a teacher quality equity law that was enacted in California in the fall of 2006 prohibiting superintendents from transferring a teacher into a school in the bottom three performance deciles of the state's academic performance index if the principal refuses the transfer. The primary mechanism through which the policy should affect student outcomes is through the mix of the quality of teachers in the school. Using publicly available statewide administrative education data, and two quasi-experimental methodologies, I assess whether the policy had an effect on the district-wide distribution of teachers with varying levels of experience, education and licensure and on student academic performance. I extend the analysis by examining whether the policy has differential effects on subgroups of schools classified as having high-poverty or high-minority student populations. I find that, as a result of the teacher quality equity law, low-performing schools experienced a relative increase in fully-credentialed teachers and more highly educated teachers, but that did not necessarily translate to an increase in academic performance. I also find evidence that the dimension along which the policy was most effective was in improving teacher pre-service qualifications in schools with high minority student populations.

In the second essay, I estimate racial, ethnic, gender and socioeconomic differences in teacher reports of student absenteeism and tardiness while controlling for administrative records of actual absences. Subjective perceptions that teachers form about students' classroom behaviors matter for student academic outcomes. Given this potential impact, it is important to identify any biases in these perceptions that would disadvantage subgroups of students. I use longitudinal data from the Early Childhood Longitudinal Study, Kindergarten Class of 1998-99 in conjunction with longitudinal, student-level data from the North Carolina Education Data Research Center to employ a variation of a two sample instrumental variables approach in which I instrument for actual eighth grade absences with simulated measures of eight grade absences. I find consistent evidence that teacher reports of the attendance of poor students are negatively biased and that math teacher reports of male attendance are positively biased. There is mixed evidence with regard to student race and ethnicity.

The third essay is a co-authored work in which we employ a quasi-experimental estimation strategy to examine the effects of state-level job losses on fourth- and eighth-grade test scores, using federal Mass Layoff Statistics and 1996-2009 National Assessment of Educational Progress data. Results indicate that job losses decrease scores. Effects are larger for eighth than fourth graders and for math than reading assessments, and are robust to specification checks. Job losses to 1 percent of a state's working-age population lead to a .076 standard deviation decrease in the state's eighth-grade math scores. This result is an order of magnitude larger than those found in previous studies that have compared students whose parents lose employment to otherwise similar students, suggesting that downturns affect all students, not just students who experience parental job loss. Our findings have important implications for accountability schemes: we calculate that a state experiencing one-year job losses to 2 percent of its workers (a magnitude observed in seven states) likely sees a 16 percent increase in the share of its schools failing to make Adequate Yearly Progress under No Child Left Behind.

This dissertation explores the relationship between external shocks local labor markets and entrepreneurship. The first and main essay investigates the effects of a large firm's geographical expansion (anchor firm) on local worker transitions into startup employment through wage effects in industries economically proximate to the anchor firm. Using hand collected data on large firms' site searches matched to administrative Census microdata, I exploit lists of anchor firms' site selection process to employ a difference-in-differences approach to compare workers and employers in winning counties to those in counterfactual counties. Counties are balanced along a number of socio-economic characteristics as well as ex ante industry distribution, firm size distribution, and firm age distribution. The arrival of an anchor firm induces entrepreneurship in industries linked through input-output channels by a magnitude of 120 new establishments that account for over 2,300 jobs. Relative to young firms in counterfactual counties, these new firms grow 12% faster in five-year employment growth and have a 7% lower failure probability. These effects are strongest in the most specialized and knowledge-intensive industries. Attracting an anchor firm to account appears to have limited spillover effects in employment that are mainly driven by reorganization of incumbent firms in input-output industries with occupational similarity of the anchor firm that face rising labor costs.

The second essay provides a blueprint for understanding the dynamics surrounding mass layoffs and business closures. This essay creates a novel data set linking geocoded Business Registration data to public layoff notifications data. This data can be used to understand how local entrepreneurship can reduce unemployment spells and earnings penalties for low wage displaced workers. Workers eventually employed by startups experience faster post-displacement wage growth than those eventually employed by mature firms. In final essay, I provide motivation for research investigating the spatially heterogeneous effects the advancement of certain industries inhibit entrepreneurship in others. I decompose a Bartik employment measure of demand for a region's labor. The decomposition shows that the recovery from the Great Recession was led by capital-intensive industries (e.g., transportation manufacturing and machinery manufacturing) that are typically inversely associated with local entrepreneurship. Interestingly, the inverse association of these industries and entrepreneurship appears to spillover into other industries. These industries include transportation equipment manufacturing and machinery manufacturing. This set of observations motivates this dissertation's research agenda to understand the cross-industry relationships that drive an area's level of entrepreneurship and labor market dynamism.

This dissertation studies three questions in which economic behavior at the firm level plays an important role. Chapter 2 studies how individual owner-managers shape firm conduct in the labor market. I use survey and administrative microdata from the U.S. Census to link firm and worker outcomes to the past local unemployment rate exposure (URE) of owner-managers. Using a difference in differences approach centered on changes in firm ownership, I find that firms acquired by high URE owner-managers increase worker earnings on average while displaying no differential trends in firm employment. These results also hold in worker-level analysis, which reveals that firm-level differences are driven in part by immediate pay increases for older and more educated workers, resulting in greater retention among these cohorts. These results are further validated among firms that do not experience ownership changes. Using an instrumental variables design, I find that URE is associated with greater rent-sharing at the firm level. Together, these results demonstrate that owner-managers have substantial scope to determine pay and hiring policy at their firms.

Chapter 3, coauthored with Mark Curtis, Daniel Garrett, Eric Ohrn, and Juan Carlos Suarez Serrato, studies plant-level responses to a large federal tax incentive, known as bonus depreciation, that lowered the cost of capital investment. Difference-in-differences estimates using confidential Census Data on manufacturing establishments show that tax policies increased both investment and employment, but did not stimulate wage or productivity growth. Using a structural model, we find that the primary effect of the policy was to increase the use of all inputs by lowering costs of production and that capital and production workers are complementary inputs in modern manufacturing. Our results show that tax policies that incentivize capital investment do not lead manufacturing plants to replace workers with machines.

The fourth chapter assesses how state and local taxes influence firm entry decisions in the video gambling industry in Illinois, which comprises almost 7,000 establishments each operating up to five slot machine-like gambling terminals. Using variation in local gambling ordinances and an event-study framework, I estimate that gambling legalization leads on average to a 3.0% increase in local tax revenue and a noisy 1.6% increase in local spending. I then develop and estimate an equilibrium model of entry and exit to explore the effects of counterfactual tax increases. Simulations reveal that uniform increases in the marginal tax rate increase tax revenue while reducing the extent to which gambling establishments select into low-income neighborhoods. Taken together, these results suggest that taxation can effectively offset the regressivity of gambling activity if revenue is effectively targeted to local governments.

Over my Ph.D. study, I work on various projects about the school choice reform in New York City, with a special focus on understanding how students or parents choose high schools and evaluating education policies. Specifically, my dissertation consists of two essays: the first one aims to detect whether small schools are effective in improving students' academic performance; the second one measures how one's own school choice is affected by his or her neighbors.

In the first chapter, which is coauthored with Atila Abdulkadiroglu and Parag Pathak, We use assignment lotteries embedded in New York City's high school match to estimate the effects of attendance at a new small high school on student achievement. More than 150 unselective small high schools created between 2002 and 2008 have enhanced autonomy, but operate within-district with traditional public school teachers, principals, and collectively-bargained work rules. Lottery estimates show positive score gains in Mathematics, English, Science, and History, more

credit accumulation, and higher graduation rates. Small school attendance causes a substantial increase in college enrollment, with a marked shift to CUNY institutions. Students are also less likely to require remediation in reading and writing when at college. Detailed school surveys indicate that students at small schools are more engaged and closely monitored, despite fewer

course offerings and activities. Teachers report greater feedback, increased safety, and improved collaboration. The results show that school size is an important factor in education production

and highlight the potential for within-district reform strategies to substantially improve

student achievement.

In the second chapter, I use the exact home addresses and the complete high school application records to estimate neighborhood impact on the choice of high schools in the New York city. This paper converts home addresses to location coordinates and exploit that metric to rank students' neighbors by distance and estimate the marginal influence of the school choice of the immediate (ten nearest) neighbors relative to that of more distant neighbors. With the assumption that one's immediate neighbors are formed roughly randomly within the reference group, I find that students are 20\% more likely to rank the identical schools as their immediate neighbors than their more distant neighbors. The estimated effects are stronger among students with homogeneous ethnic and academic backgrounds. For a robustness check, I match the home addresses with the 2010 census data to group students into different census blocks and block groups. This alternative definition of neighborhood peers by census geographic boundaries further confirms the existence of social interactions on school choice. Further, I study if elder neighbors' experience of school choice benefits younger neighborhood peers. On one hand, information sharing can be beneficial: experience from older students improves their nearest neighbors' probability of being matched with their top choice. On the other hand, inefficient herding for students living in the less informed areas can be a disadvantage of neighborhood interactions.