Browsing by Author "Arcidiacono, Peter"

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.

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 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.

This dissertation presents two essays in labor economics. In the first essay, I study employer learning in a labor market with dynamic statistical discrimination on the basis of time-varying worker characteristics such as marital status. In the second essay, I explore the relationship between workplace flexibility and worker and occupation characteristics. These essays provide insights into the information frictions in the labor market and the cost of providing job amenities.

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 analyzes the effects of various inputs in the education production function on student outcomes in higher education. Using unique data from public higher education in Arkansas, this paper uses student-level analysis to understand effects interactions between students with peers and instructors on college and labor market outcomes. The first chapter analyzes the effects of college peer referrals on labor market outcomes, as well as how these effects differ by gender. Using a novel two-step research design, I first identify classroom network effects by exploiting quasi-random variation in section enrollment within courses. Results indicate taking a class with a peer increases the propensity for a student to get a job at a firm where the peer is incumbent. The overall propensity to use classmates in job finding does not differ by gender, although students display an increased propensity to form networks with same-gender peers. In the second step of the research design, I investigate the labor market effects of obtaining a job through a classmate. Consistent with the predictions of a referral-based job search model, workers who obtain jobs through classmates earn more and are less likely to leave the firm, and effects decline with tenure in the firm. Furthermore, while referrals benefit both genders, the earnings premium from referrals for women is less than half the premium for men. From a policy perspective, these findings suggest a key tradeoff between increasing efficiency through referrals and increasing gender equity. The second paper looks at the relative effects of full-time versus adjunct instructors on student outcomes in college. I focus on students in their first semester of college and employ an identification strategy that exploits within-student variation in instructor type teaching courses, as well as within-course variation of instructors teaching a given course. I find that students have a students have a lower propensity of taking another course in the subject when the course is taught by an adjunct, compared to a full-time instructor, and students with a higher proportion of adjunct instructors in their first term of college are less likely to graduate on time. Additionally, for instructors who switch statuses, moving from adjunct to full-time increases both propensity that their students will take a subsequent course in the subject, as well as the propensity of students retention to a second year of college. Taken together, these results suggest that institutional differences in the treatment of part-time vs. full-time workers contribute to differences in labor output, independent of inherent differences between part-time vs. full-time workers.

This dissertation presents three essays on the topic of the economics of education. In the first essay, I examine the importance of family shocks for student learning. In the second, I describe how the evolution of the Hispanic-white test score gap varies by immigrant generation. The last essay explores the racial divide in education and the labor market through evidence from interracial families.

This dissertation presents three essays on topics that lie at the intersection of development and labor economics. The essays relate to poverty and inequality in the United States and internationally, focusing on labor markets, housing markets, and human capital. The first essay sheds light on how land use regulation affects local economic development, operating through local housing and labor markets. I study this topic in the context of federally recognized American Indian reservations, where land tenure categories include fee simple land, which is free from transaction restrictions, and trust land, which is held in trust by the US federal government and associated with restrictions on transactions. Drawing on a range of hard-to-access microdata products, my analysis indicates that land use regulation lowers local wages and employment but that it is possible to foster economic development without changing the status of the land. In fact, land use regulation increases the likelihood that the local population benefits from demand-driven, place-based policies. Using casino adoption on reservations as local labor demand shocks, I find that reservations with a larger share of land in trust experience larger increases in real wages following economic shocks. The second essay paints a picture of poverty in rural America with a particular focus on relating the Black-White wealth differential to the Black-White human capital differential. Using a low-asset subgroup of the rural population, I show that when the wealth gap narrows, we are less likely to observe racial heterogeneity in rates of high school completion and teenage motherhood. This essay establishes two important insights that help explain the observed race gaps in cities: (i) Black-White differences in wealth are much larger in urban areas than rural areas, and (ii) household income may not accurately reflect poverty. The third essay turns to poverty in low-income countries, focusing on labor market frictions and employment outcomes in South Africa. In this essay, I describe the design and implementation of a large-scale field experiment that tests whether an online professional networking platform changes the labor market engagement of youth. Specifically, my co-authors and I test whether training young work-seekers to use LinkedIn improves their employment outcomes. We find that the LinkedIn treatment rapidly increases employment at the extensive margin.

This dissertation considers the relationship between peer and individual student interaction. The central finding is that self reported friends play a crucial role in individual behaviors, a role that is more significant than other students in their school. Also, using the network of friendships within a school it is possible to construct new peer effect measures and account for endogenous peer group formation. It is however important to distinguish these peer measures from unobserved individual characteristics that may also influence behavior.

The first chapter examines the effect of potentially misidentifying the reference group on peer effect estimates. The differential impact of school, grade and friend level peer effects on student decisions to smoke and drink are calculated. Friendship nominations come from the Add Health dataset, where students can list up to 10 friends from the school. The bias due to endogenous peer group formation and simulteneity are considered using various instrumenting strategies. Peer effects are found to be large and significant at the friends level for both delinquency variables. It is possible to show that misidentifying the peer group can result in peer effect estimates that are understated by as much as 40\%.

The second chapter of the dissertation further examines the role of peer interactions, this time considering the effect of popularity on student academic achievement. Recent work has found a strong positive relationship between these variables. In this chapter I ascertain the robustness of these previous findings to controls for unobserved student heterogeneity using and instrumenting technique and a structural model. The results indicate that popularity influences academic achievement positively in the baseline model. However, instrumenting for popularity or including measures of unobserved student characteristics results in a large drop in the effect of popularity, and leads to a significantly negative coefficient in the majority of cases. Interestingly, popularity influences future earnings and attitudes positively, where this effect is robust to the inclusion of unobserved type. Policy simulations where students are redistributed based on race or income indicate that the predicted number of friendships and popularity fall but academic achievement increases. Since student popularity increases happiness and earnings, the overall effect of the redistribution policies have to be considered before implementation.

Female underrepresentation in STEM fields is, in part, driven by gender differences in pre-college academic preparation. Female and male students take different courses in high school, leading to different college majors and occupations. This dissertation studies decisions about which courses to take in high school, to better understand how students select into different levels of pre-college academic preparation.

The second chapter presents evidence of gender differences in intended college major among high school students in North Carolina, the sample I study throughout this dissertation. Boys are more likely to intend to major in a STEM field, though girls make up the majority of Biology and Pre-Medicine majors. Gaps in STEM majors cannot be explained by differences in ACT scores. In addition to being more interested in STEM, boys are less certain of their intended major.

The third chapter focuses on students' decisions about which math classes to take in high school. After controlling for course grades and ability, I find large gender differences in the decision of whether to take Precalculus after Algebra 2. Boys are significantly more likely to take Precalculus than girls with comparable academic performance. Gender gaps widen over the course of the math curriculum. I propose some possible explanations for these results, including gender differences in comparative advantage and effort, which would affect the costs and benefits associated with taking advanced classes.

In the fourth chapter, I estimate a model of course selection in math and English in order to understand the drivers of gender differences in high school coursework. In the model, students choose a bundle of courses to take instead of considering each subject independently. Relaxing the independence assumption allows me to explore whether gender differences in the costs of bundling multiple advanced classes can explain the observed sorting patterns into advanced classes. The results indicate that, while gender differences in ability, past academic performance, and preferences for math and English play a larger role, gender differences in bundling costs do contribute to gender differences in course selection patterns.

At least since the seminal works of Jacob Mincer, labor economists have sought to understand how students make higher education investment decisions. Mincer’s original work seeks to understand how students decide how much education to accrue; subsequent work by various authors seeks to understand how students choose where to attend college, what field to major in, and whether to drop out of college.

Broadly speaking, this rich sub-field of literature contributes to society in two ways: First, it provides a better understanding of important social behaviors. Second, it helps policymakers anticipate the responses of students when evaluating various policy reforms.

While research on the higher education investment decisions of students has had an enormous impact on our understanding of society and has shaped countless education policies, students are only one interested party in the higher education landscape. In the jargon of economists, students represent only the `demand side’ of higher education---customers who are choosing options from a set of available alternatives. Opposite students are instructors and administrators who represent the `supply side’ of higher education---those who decide which options are available to students.

For similar reasons, it is also important to understand how individuals on the supply side of education make decisions: First, this provides a deeper understanding of the behaviors of important social institutions. Second, it helps policymakers anticipate the responses of instructors and administrators when evaluating various reforms. However, while there is substantial literature understanding decisions made on the demand side of education, there is far less attention paid to decisions on the supply side of education.

This dissertation uses empirical evidence to better understand how instructors and administrators make decisions and the implications of these decisions for students.

In the first chapter, I use data from Duke University and a Bayesian model of correlated learning to measure the signal quality of grades across academic fields. The correlated feature of the model allows grades in one academic field to signal ability in all other fields allowing me to measure both ‘own category' signal quality and ‘spillover' signal quality. Estimates reveal a clear division between information rich Science, Engineering, and Economics grades and less informative Humanities and Social Science grades. In many specifications, information spillovers are so powerful that precise Science, Engineering, and Economics grades are more informative about Humanities and Social Science abilities than Humanities and Social Science grades. This suggests students who take engineering courses during their Freshman year make more informed specialization decisions later in college.

In the second chapter, I use data from the University of Central Arkansas to understand how universities decide which courses to offer and how much to spend on instructors for these courses. Course offerings and instructor characteristics directly affect the courses students choose and the value they receive from these choices. This chapter reveals the university preferences over these student outcomes which best explain observed course offerings and instructors. This allows me to assess whether university incentives are aligned with students, to determine what alternative university choices would be preferred by students, and to illustrate how a revenue neutral tax/subsidy policy can induce a university to make these student-best decisions.

In the third chapter, co-authored with Thomas Ahn, Peter Arcidiacono, and Amy Hopson, we use data from the University of Kentucky to understand how instructors choose grading policies. In this chapter, we estimate an equilibrium model in which instructors choose grading policies and students choose courses and study effort given grading policies. In this model, instructors set both a grading intercept and a return on ability and effort. This builds a rich link between the grading policy decisions of instructors and the course choices of students. We use estimates of this model to infer what preference parameters best explain why instructors chose estimated grading policies. To illustrate the importance of these supply side decisions, we show changing grading policies can substantially reduce the gender gap in STEM enrollment.

This dissertation consists of two separate essays on major choice in higher education. In the first chapter, I investigate how differences in information affect students' major choices over time. Since college has such a short time horizon, the amount of information students have before coming in may play a big role in how well they are matched to their final major. They may also choose their initial major based on how uncertain they are about their match with that major, especially since they have the option to switch in future periods. This paper discusses students' search process in finding a major, and how information impacts behavior and ultimate outcomes. I set up a tiered structure where the student must first choose a field (either STEM or Non-STEM) and then choose a major within that field. This allows for matches within a particular field to be correlated, thus providing information on non-chosen majors within the same field. The student makes decisions based on the choices that will maximize her expected utility over her entire college career. Since her current choices and information set depend on past decisions, and since there are a finite number of periods, I can solve the dynamic decision problem using backwards recursion.

Once I solve for the student's optimal decision path, I estimate the model using data from the Campus Life and Learning Survey from Duke University. The CLL data allows me to observe students' expected majors at multiple points throughout their college career. I attempt to find the model parameters that best match particular moments in the data. The first key type of moment involves overall switching patterns, that is, the probability of choosing a particular field in the initial period, and then the probabilities of later decisions conditional on the first choice. The second key type of moment I match captures which students are making which decisions. I look at how academic ability, as measured by SAT Math scores, and gender affect the choice probabilities in the data.

I find that the STEM field has a much lower average match value than non-STEM, but a higher variance in matches. Thus, students are less certain about how well they might match with STEM. Students with higher math ability are more likely to choose STEM in the first period, but the sorting by ability greatly increases in the later period. It is costly to switch into STEM from non-STEM in the second period, while the reverse move is virtually costless. All of these results support the theoretical result that students will choose the field with more uncertainty in the early periods (given similar expected match values) because of the option to switch later if they get a bad match. This is especially true when the more uncertain field is also more costly to switch into in later periods, as in the case of STEM.

In the second chapter, co-authored with Thomas Ahn, Peter Arcidiacono, and James Thomas, we estimate an equilibrium model of grading policies. On the supply side, professors offer courses with particular grading policies. Professors set both an intercept and a return to studying and ability in determining their grading policies. They make these decisions, attempting to maximize their own utility, but taking into account all other professors' grading policies. On the demand side, students respond by selecting a bundle of courses, then deciding how much to study in each class conditional on enrolling. We allow men and women to have different preferences over different departments, how much they like higher grades, and how costly it is to exert more effort in studying.

Two decompositions are performed. First, we separate out how much of the differences in grading policies across fields is driven by differences in demand for courses in those fields and how much is due to differences in professor preferences across fields. Second, we separate out how much differences in female/male course taking across fields is driven by i) differences in cognitive skills, ii) differences in the valuation of grades, iii) differences in the cost of studying, and iv) differences in field preferences.

We then use the structural parameters to evaluate restrictions on grading policies. Restrictions on grading policies that equalize grade distributions across classes result in higher (lower) grades in science (non-science) fields but more (less) work being required. As women are willing to study more than men, this restriction on grading policies results in more women pursuing the sciences and more men pursuing the non-sciences.

This dissertation studies the supply of charter schools, school alternatives introduced to education markets to expand choice for students. Drawing upon unique data gathered from Florida, the chapters examine the characteristics and behavior of charter schools and their implications for equilibrium sector outcomes and for policy. The first chapter investigates how non and for-profit managed charter schools differ in terms of where they locate, the composition of students they serve, and student performance. Regression estimates indicate that, among independent charters, for-profits spend less per pupil on instruction and achieve lower student proficiency gains. By contrast, among charter schools that belong to a network, for-profits spend significantly less per pupil, but expenses on student instruction are not being cut. These results thus provide empirical evidence concerning the trade-offs surrounding recent policies that restrict for-profit management of charter schools. The second chapter develops and estimates an empirical model of how charter schools decide where to locate in a school district. This is motivated by the possibility that flat funding formulas create an incentive for charter schools to spatially ``skim'' low-cost students. In the model, charter schools choose a location based on expected revenues, which depend on the per-pupil funding rate, and costs, which depend on the composition of students served. The equilibrium structure of the model, which embeds competition with public and other charter schools for students, facilitates the study of counterfactual funding policies, including a formula tying revenue to the characteristics of students a charter school serves. The estimation strategy consists of linking charter school effectiveness at raising student achievement, recovered from student test score data, with charter school expenditures to estimate the cost structure of charter schools and then leveraging revealed preference to uncover how charter schools respond to competitive and financial incentives. The results indicate that a cost-adjusted funding formula would significantly increase the share of charter schools serving disadvantaged students with little reduction in aggregate effectiveness. These findings are important in demonstrating that a mismatch between funding and costs may generate significant disparities in benefits from school choice through inequity in access. Together, the chapters suggest that supply-side incentives may provide an effective policy instrument for directing competition in education markets, which has broad implications for the design of school choice programs.

This dissertation considers incentives arising from equilibrium influences that affect the sequence of decisions that lead to family formation. The first chapter examines how state regulations directly aimed at abortion providers affect the market for abortion in the United States. Estimates from a dynamic model of competition among abortion providers show that regulations' main impact is on the fixed costs of entry for providers. Simulations indicate that the removal of regulations would promote entry and competition among abortion providers, and because abortions are found to be price sensitive, this would lead to increases in the number of abortions observed. The second chapter tests if an important negative externality of abortion access exists, namely whether abortion access makes prospective fathers more likely to leave pregnant women. Designing a number of empirical tests, I confirm that in some areas where abortion is more accessible women who give birth are more likely to be single mothers, rather than sharing parental responsibility with the biological father. The final chapter, which is joint work with Peter Arcidiacono and Marjorie McElroy, examines how gender ratios influence bargaining power in romantic relationships between men and women. Gender ratios, by influencing the prospects of matching, allow us to estimate preferences for various match characteristics and activities. We find men prefer sexual relationships more than women at high school ages, and that men and women trade off their preferred partner for an increased chance of matching.

The rigorous economic analysis of peer group formation is a burgeoning subject. Much has been written about how peers influence an individual's behavior, and these effects are quite prevalent. However, less has been written on how exactly these peer groups begin and the resulting consequences of their formation. A reason for the dearth of knowledge on peer group formation is the lack of quality data sets that clearly define one's peers. To resolve this issue, the first chapter of this document explores data which allows a peer group to be defined openly through self nominations. Using these nominations as well as characteristics of the students and their friends, it is possible to see on what dimensions these individuals are sorting into friendships. The data suggests that there is heavy sorting within race and academic ability. Additionally, tests for statistical discrimination on race and academics show that it is exhibited towards blacks and Hispanics. There is also weak evidence of statistical discrimination against whites. Empirical analysis also shows that the degree of statistical discrimination decreases for blacks and Hispanics over a year; however, there is little change for whites over the same period. This result suggests a process of learning about a noisy signal on academic characteristics. Once a peer group is formed, however, the effects of the peer group become much more interesting. The second chapter of this document attempts to find an effect of having friends of a similar race and who are involved in similar activities. Using a strategy that corrects for the endogeneity of peer effects by instrumenting using variables at the ``grade within school'' level, it is shown that friendship diversity can help whites increase achievement. Although not much significance was found with other races, most of the strategies pushed towards the direction of racial diversity aiding achievement. Regarding extracurricular activities, it is found that there is a benefit in having friends in common individual academic activities, conditional on the respondent only belonging to academic or scholastic clubs. There are insignificant effects in having friends in common sports, conditional on the respondent only participating in sports. Potential future work for both chapters can include models describing the benefit of having various friends and the probability of forming those friendships, which can be used to simulate redistribution policies.

This dissertation is comprised of two chapters in the intersection of health and labor economics. In Chapter 1, I describe the patterns between utilization of mental health care and socioeconomic status, as observed in the administrative data-set obtained from Hungary. In line with existing literature, I find that women, older individuals and those in lower wage deciles use more antidepressants, are more likely to go to psychiatric outpatient facilities and are more often hospitalized with psychiatric reasons. Mental health care utilization is also more likely for those with more unemployed months. In addition to the describing the patterns between utilization and individual characteristics, I also examine the geographical variations. Furthermore, I include a description on the effects of the loss of exclusivity of escitalopram, a main ingredient in the antidepressant markets. I find that the loss of exclusivity seems to affect poorer regions more. These regions have higher antidepressant use to begin with, but lower shares of escitalopram use, which increases more after the loss of exclusivity in these regions.

Chapter 2 is based on a collaborative work with Peter Elek. In our research we examine whether increasing access to mental health treatment improves job market outcomes. Specifically, we analyze if having psychiatric outpatient care closer to individuals improves the likelihood of employment of working age adults. We analyze a large administrative dataset from Hungary that links job histories with medical care utilization data between 2009-2017. New outpatient service locations were established in Hungarian micro-regions in 2010-2012, which had lacked such capacities before. This creates quasi-experimental variation in access to treatment that our analysis exploits. In line with existing literature, we find that more access increases healthcare utilization. Psychiatric outpatient visits increase by around 16\% and antidepressant-use increases by 8\% for working age adults compared to the matched control group. We find no evidence that hospitalization rates would fall for working age adults. We also find no evidence of the increased access having a positive effect on employment outcomes.