Economics Theses and Dissertations

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Essays on the Macroeconomic and Measurement Consequences of Government Systems
(2024) Navarrete, Michael Alexander; Hellerstein, Judith; Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
In Chapter 2, I study the macroeconomic consequences to delaying a fiscal stabilizer. Specifically, I study how delays to unemployment insurance benefits during the pandemic recession (fiscal stabilizer) affected consumption (macroeconomic consequence). The United States experienced an unprecedented increase in unemployment insurance (UI) claims starting in March 2020. State UI-benefit systems were inadequately prepared to process these claims. In states that used an antiquated programming language, COBOL, to process claims, potential claimants experienced a larger increase in administrative difficulties, which led to longer delays in benefit disbursement. Using daily debit and credit card consumption data from Affinity Solutions, I employ a two-way fixed-effects estimator to measure the causal impact of having an antiquated UI benefit system on aggregate consumption. Such systems led to a 2.8-percentage-point decline in total credit and debit card consumption relative to card consumption in states with more modern systems. I estimate that the share of claims whose processing was delayed by over 70 days rose by at least 2.1 percentage points more in COBOL states relative to non-COBOL states. Based on a back-of-the-envelope calculation using 2019 data, my results suggest that the decline in consumption in COBOL states in 2020 after the pandemic-emergency declaration corresponds to a real-GDP decline of at least $105 billion (in 2019 dollars). In Chapter 3, Joonkyu Choi, Samuel Messer, Veronika Penciakova, and I study how business formation patterns in 2020 were affected by antiquated UI benefit systems. New business formation surged after the pandemic recession, but the causes of this surge are not well understood. The expansion of UI benefits under the CARES Act, coupled with the reduction of work search, provided unemployed potential entrepreneurs with the funds and time needed to develop business ideas. States that used an antiquated programming language, COBOL, to process claims experienced a lower growth rate in UI payments per unemployed than states with more modernized systems. Using business application data from the Business Formation Statistics, we employ a two-way fixed-effects estimator to measure the causal impact of having an antiquated UI benefit system on business formation. Such systems led to a 6.6 percent decline in business applications per capita in COBOL states relative to more modernized states from March 2020 to July 2020. We also find some evidence of business quality deterioration while the Federal Pandemic Unemployment Compensation program was in effect. Our findings highlight the potential role of UI policy in contributing to economic recoveries by fostering entrepreneurship. In Chapter 4, the RESET team Gabriel Ehrlich, John Haltiwanger, David Johnson, Ron Jarmin, Seula Kim, Jake Kramer, Edward Olivares, R. Rodriguez, Mathew D. Shapiro, and I use point of sales (POS) data to construct real sales and compare these POS generated statistics to official statistics. Businesses, individuals, and government policymakers rely on accurate and timely measurement of nominal sales, inflation, and real output, but current official statistics face challenges on a number of dimensions. First, these key indicators are derived from surveys conducted by multiple agencies with different time frames, yielding a complex integration process. Second, some of the source data needed for the statistics (e.g., expenditure weights) are only available with a considerable lag. Third, response rates are declining, especially for high-frequency surveys. Focusing on retail trade statistics, we document important discrepancies between official statistics and measures computed directly from item-level transactions data. The long lags in key components of the source data delay recognition of economic turning points and lead to out-of-date information on the composition of output. We provide external data sources to validate the transactions data when their nominal sales trends differ importantly from official statistics. We then conduct counterfactual exercises that replicate the methodology that official statistical agencies use with the transactions data in the construction of nominal sales indices. These counterfactual exercises produce similar results to the official statistics even when the official nominal sales and item-level transactions data exhibit different trends.
Essays on Corporate Debt Structure and Monetary Policy Transmission
(2024) Mao, Chenyu; Kalemli-Ozcan, Sebnem SK; Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
The financing structure of firms has changed markedly over the last few decades as market-based finances have evolved. What's the role of corporate debt structure in monetary policy transmission? This dissertation delves into the heterogeneous impact of monetary policy on nonfinancial firms, examining the role of corporate debt structure in shaping transmission mechanisms. Chapter 1 explores the spillover effects of the Corporate Bond Purchase Programs on bank-dependent private firms. In particular, I study the Federal Reserve's Secondary Market Corporate Credit Facility (SMCCF) during the COVID-19 pandemic. Using a model that delineates the capital structure channel, the study shows that the spillover effects on non-targeted private firms are limited if the banking sector is not constrained. Moreover, using an event study approach with the loan and bond dataset, the study shows that SMCCF has a limited effect on private firms when its associated banks are not constrained in 2020. The results suggest that despite the implementation of the SMCCF, bank-dependent private firms experienced minimal impact, indicating the program's limited effectiveness in saturated credit markets. Chapter 2 introduces the concept of the zombie lending channel, uncovering a phenomenon where unviable firms are less affected by contractionary monetary policy due to lenders' inclination to prevent defaults by extending loans. This chapter emphasizes the importance of strengthening bank balance sheets and implementing policies to deter risky lending practices during tight financial conditions. The empirical findings illustrate that during periods of tightening monetary policy, unviable firms, colloquially termed "zombies," tend to receive continued lending support, thereby perpetuating inefficiencies within the financial system. In Chapter 3, the focus shifts to a particular dataset covering both public and private Spanish firms. The research reveals that firms with higher reliance on bank loans experience a lower interest rate pass-through during expansionary monetary policy shocks. Leverage and liquidity also play significant roles in determining heterogeneous responses to contractionary and expansionary monetary policy measures. Specifically, the results indicate that corporate debt structure significantly influences firms' responses to monetary policy shocks, with leverage and liquidity serving as critical determinants of transmission effectiveness. Through these three chapters, this dissertation provides insights into the nuanced dynamics between monetary policy, corporate finance, and financial stability, contributing to a deeper understanding of the mechanisms shaping the behavior of nonfinancial corporates in response to monetary policy initiatives.
Essays on Labor Markets
(2024) Nguyen, The Linh Bao; Urzua, Sergio; Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
The modern work landscape is undergoing a period of significant transformation. In this dissertation, I delve into three distinct, yet interconnected, themes that shed light on the complex interplay between abilities, tasks, and well-being within this changing environment. In Chapter 1, I explore the mental health implications of a recent and dramatic shift in work arrangements: the rise of Work From Home (WFH) during the COVID-19 pandemic. Specifically, the chapter evaluates the impact of working from home (WFH) on mental health, relative to other forms of workplace arrangements during the pandemic. Leveraging the longitudinal structure of the data from the British Cohort Study, the paper explores two novel dimensions that potentially influence the mental health effects of WFH, early-age cognitive and social abilities. To account for self-selection, the identification relies on a Roy selection model with correlated factors and cost-shifters. The findings suggest that WFH has negative mental health effects compared to a workplace arrangement (WP), but positive effects compared to not working (NW). Additionally, WFH has the largest detrimental impact on the mental health of individuals with lower social abilities relative to WP, and it confers the most substantial benefits on those with higher cognitive abilities compared to NW. Finally, the model predicts that investments in cognitive and social ability mitigate the cost and amplify the benefits associated with WFH. Next, in Chapter 2, I shift the focus to a contentious education policy that has recently received much attention, affirmative action in education. In this chapter, I examine the impacts of an education affirmative action policy on not only education outcomes, but also later labor market outcomes, in the context of Vietnam. In particular, the policy in this study provides nationwide direct high school admissions to ethnic minority students, exempting them from taking a high-stakes high school entrance exam. Using the joint variation in the student's ethnicity and birth year in a difference-in-differences framework, I show that the policy improves the probability of entering high school for ethnic minorities. Further, leveraging this policy-induced variation as an instrument, I explore the policy's long-term effects on labor market outcomes. The results indicate that ethnic minority students who were encouraged to enter high school by the policy are more likely to participate in the labor force, obtain employment, and hold salaried positions. The analysis of occupation-specific skill distributions and task intensity suggests that these effects are likely attributable to the human capital channel rather than education signaling. Despite its overall benefits, the policy's impacts are not equally distributed across the gender line and wealth levels: Male and wealthy ethnic minority students benefit more from the policy. Using a random forest model to identify the compliers' characteristics confirms that future family concerns among females and financial constraints are major frictions for ethnic minorities to benefit from the policy. Overall, these results suggest that while affirmative action positively impacts education and labor outcomes for ethnic minorities, targeted policies are vital for equitable distribution, addressing gender and financial barriers. Finally, Chapter 3 closes the discussion on the topic of tasks and skills at the critical early career stages. The early stages of one's career are a dynamic period of exploration and skill development not only from formal training but also through on-the-job tasks. Therefore, the paper explores the pivotal relationship between abilities and tasks during this time. Specifically, it investigates how cognitive, social, and manual abilities are rewarded in this crucial period, while also emphasizing the role of abilities in sorting individuals across task-based occupations. The paper employs the British Cohort Study 1970 in a Roy selection model with correlated factors. In this context, the Roy model allows the analysis to focus not only on the returns to abilities, but also on the sorting process within the context of occupations categorized by their task composition. The results reveal a task-specific nature in the returns to abilities during early career stages, emphasizing the importance of aligning abilities with the specific task requirements of chosen occupations for optimal rewards. Additionally, the paper also highlights the role of abilities in early career sorting, showing that individuals with high cognitive and social abilities tend to gravitate towards knowledge-based occupations - occupations that are characterized by intensive cognitive tasks or intensive social tasks. These findings offer valuable insights for both young individuals navigating their career paths and policymakers crafting programs aimed at facilitating informed decision-making and enhancing success in the early career landscape.
Essays on Economics of Education
(2024) Morales Lema, Catalina; Urzúa, Sergio; Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
In this dissertation, I use data from Chile to study the determinants of schooling trajectories. Chapters 1 and 2 focus on higher education, Chapter 3 on secondary education, and Chapter 4 on teachers. Chapter 1 explores the role of a socio-emotional ability, self-efficacy, in understanding why students with comparable qualifications transit different college paths. This study is the first of two papers dedicated to studying the role of self-efficacy in the path students follow after high school. This first paper discusses the psychology literature on self-efficacy and how it can be measured. Then, through exploratory factor analysis and rich administrative data from Chile, I show that self-efficacy is a construct different from pure cognitive ability. Finally, I estimate a discrete choice model for the decisions of taking the college admissions test, applying, enrolling, and graduating from college. I find that conditional on cognitive ability, a higher self-efficacy increases the probability of taking the college admissions test, applying, and graduating from college within eight years. Analyzing heterogeneous effects, I find a bigger effect among students from low-SES families, which are precisely the ones with lower base levels of these outcomes. In Chapter 2, I take a step further and explicitly model the role of self-efficacy on the trajectories students follow after high school using a structural approach. I estimate a multi-stage discrete choice model with unobserved heterogeneity to study the role of self-efficacy on college applications, enrollment, and graduation decisions. The results indicate that higher self-efficacy significantly increases the likelihood of taking the college admissions exam and submitting a college application, conditional on cognitive ability. For students who apply, increasing self-efficacy also increases their probability of enrolling in and graduating from college, even more than a comparable increase in cognitive ability. From the analysis of socioeconomic groups, I document that improving students' self-efficacy could reduce the socioeconomic gaps in the percentage of students who take the college admissions test, apply, and enroll in college. These findings suggest that policies oriented to boost students' self-efficacy could alleviate income-related inequalities in access to higher education. Chapter 3 is co-authored with Dr. Daniel Kraynak and Dr. Cristina Riquelme. It investigates how local economic conditions impact human capital accumulation in Chile's copper-producing zones using high-frequency data on copper prices, school attendance, and academic performance. To measure the exposure to copper price volatility, we created an index by determining the proportion of workers in the area associated with the metal mining industry. We performed a difference-in-differences analysis by comparing students in areas with low and high copper exposure during periods of varying prices. The results indicate that increasing copper prices in more exposed areas decreases the quarterly attendance of high school students in the same period. We also find that students compensate for this lower attendance by increasing their attendance in the next quarter. Analyzing test score performance, we find evidence of a positive effect of local economic conditions on students' math performance in the same period. However, this effect is completely offset in the following year. Chapter 4 is co-authored with Dr. Macarena Kutscher, Dr. Cristina Riquelme, and Dr. Sergio Urzúa. It explores the contribution of teachers to student performance in Chile's college admission test (PSU). Our analysis is based on a unique teacher-student matched dataset and decomposition methods. The findings suggest that teachers' performance on the PSU and the characteristics of their educational degrees are significant predictors of students' success. When controlling for students' and predetermined school characteristics, the gap between vouchers and public schools is reduced. Productivity differences emerge as key factors driving the disparities across school types. The analysis underscores the crucial role of teacher-student interactions in shaping student outcomes.
Essays on Higher Education
(2024) Montoya Agudelo, Alejandra; Urzúa, Sergio; Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
In this dissertation, I quantify the impact of uncertainty on schooling postsecondary choices, study the returns to higher education degrees, and analyze the effects of policies that intend to reduce college education costs. In the second and third chapters, I employ structural Roy models and data from the National Longitudinal Survey of Youth 1997 to analyze postsecondary schooling decisions, focusing on four- and two-year college paths. These models have three sources of unobserved heterogeneity affecting earnings and decisions: cognitive, socioemotional, and mechanical latent abilities. The second chapter employs a dynamic Roy model to quantify the impact of uncertainty when making postsecondary schooling. While schooling choices maximize expected value, some individuals opt for alternatives that, in hindsight, do not yield the highest ex-post net value due to idiosyncratic shocks affecting earnings and schooling costs that are unknown when decisions are made. This uncertainty generates significant losses: I estimate that aggregate net value would increase by 11% if individuals had perfect foresight. Moreover, I study how decisions would change under perfect foresight and characterize individuals more likely to be affected by uncertainty. I also explore policy simulations to study the effects of an annual two-year college $16,500 subsidy, including the characterization of compliers—those more likely to attain a two-year college degree because of the subsidy. The third chapter analyzes the interplay of observed and unobserved dimensions as determinants of marginal treatment effect (MTEs) through decomposition analysis. We posit a static Roy model with unordered schooling choices. We focus on MTEs as they shape other treatment effects and capture the impact for those responding to minimal incentives. Additionally, we estimate the model separately for women and men, focusing on describing how responses and treatment effects vary between these two groups. We find different ability distributions and returns to ability for women and men. Moreover, we document how different observed characteristics and ability dimensions play different roles in determining the heterogeneity observed in MTEs across both groups. The last chapter investigates the impact of financial aid programs on high-quality private colleges' decisions, leveraging exogenous variation from a large-scale aid program in Colombia, where beneficiaries could only enroll at high-quality colleges. Using a difference-in-differences strategy and data for all private colleges in the country, we find that tuition increased by about 6.9 percent after the government launched the aid policy. We contribute to the literature by analyzing the effect of financial aid programs on tuition for high-quality universities and studying how universities might change other outcomes beyond tuition in response to the policy. We show universities hire more faculty members, keep the student-to-faculty constant, and open new undergraduate programs. Our findings support a narrative where prestigious colleges prioritize their reputation, opting for gradual expansion without compromising quality.
Essays on Voter Behavior and Party Representation
(2024) Perilla Garcia, Jorge Enrique; Kaplan, Ethan; Drazen, Allan; Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
In this dissertation I study how political agents such as voters and corporations behave in a context of increasing political polarization. I investigate the role that access to power has on the electoral performance of radical parties, the effect of racial unrest in the United States on campaign contributions, and whether political giving by corporations and individuals has polarized in recent years. In the last few decades, radical parties have become increasingly important in Europe and Latin America. These parties often adopt policies that depart from the mainstream economic consensus and may threaten democratic institutions. In chapter 2 of this dissertation, I explore the role that the incumbency effect may play in the success of far-right and far-left parties in Europe and Latin America. I find that, on average, and in a sample of municipal council elections held in Colombia, Sweden, Finland, Spain, and Brazil, radical parties enjoy an incumbency advantage that is as large as that of non-radical parties. To estimate these effects, I compare elections where parties marginally win or lose an additional seat in the council. This study provides suggestive evidence that far-left parties have a larger incumbency advantage than far-right parties. The wide heterogeneity of far-right parties in Sweden and Colombia is the primary driver of this difference. I posit that the difference in question could be attributed primarily to the far-right Sweden Democrats’ nonparticipation in coalitions in municipal governments and the absence of an effect of incumbency on the probability of running again for political parties in Sweden. The findings from this chapter suggest that the normal course of the democratic process may lead to radical parties encroaching on positions of power. In chapter 3, I study the effect of racial unrest on campaign contributions and how this effect is mediated by media coverage. Using a regression discontinuity in time, I find that political donations increased after the killing of George Floyd in May 2020. Exploiting discontinuities in media market borders in the United States I find that counties that were more exposed to coverage of the protests by a TV station owned by Sinclair, a conservative media conglomerate, were less likely to support Republican candidates. I provide suggestive evidence that this non-intuitive result could be the consequence of higher coverage of protests by Sinclair-owned TV stations when compared to other TV stations. By rising salience of the issue of racial tensions where Democrats were more trusted than Republicans, this increased media coverage may have depressed donations to the Republican party. I also report suggestive evidence that in counties exposed to more TV ads about police brutality there was higher support for the Democratic party than in less exposed counties. In chapter 4, in a joint work with Ethan Kaplan, Andrew Sweeting, and Yidan Xu, we measure and decompose the partisanship of corporate campaign contributions from 1990 to 2020 using a variance index approach, and provide a comparison analysis of individual donations. Despite previously documented trends towards greater partisanship in voting and political discourse, the donations of corporate PACs have remained bipartisan both in aggregate and individually. This is true across most, but not all, sectors of the economy. Individual giving is, and always has been, partisan at the individual level (individuals usually only give to one party), although there was greater partisanship in the giving of the largest individual contributors in the 2020 election. We make suggestions for future research including suggestions on how to measure other dimensions of corporate polarization which may be more salient to the public.
Essays on Mental Health, Education, and Parental Labor Force Participation
(2024) Nesbit, Rachel; Kuersteiner, Guido; Pope, Nolan; Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
This dissertation consists of three chapters in empirical microeconomics. The first chapterfocuses on mental health in the criminal justice system. I show that mandated mental health treatment during probation decreases future recidivism and further that paying for these probationers to receive treatment would be a very cost-effective program. The second chapter focuses on the labor supply of same-sex couples. My coauthors and I document the earnings patterns in same-sex couples after the entrance of their first child and contrast them with the earnings patterns in opposite-sex couples. The third chapter evaluates state-level policies to offer a college admissions exam (either the SAT or ACT) free to all high school students. I estimate precise null effects of the policies on future college attendance. The three chapters are described in further detail below. Chapter 1. Mental health disorders are particularly prevalent among those in the criminaljustice system and may be a contributing factor in recidivism. Using North Carolina court cases from 1994 to 2009, this chapter evaluates how mandated mental health treatment as a term of probation impacts the likelihood that individuals return to the criminal justice system. I use random variation in judge assignment to compare those who were required to seek weekly mental health counseling to those who were not. The main findings are that being assigned to seek mental health treatment decreases the likelihood of three-year recidivism by about 12 percentage points, or 36 percent. This effect persists over time, and is similar among various types of individuals on probation. In addition, I show that mental health treatment operates distinctly from drug addiction interventions in a multiple-treatment framework. I provide evidence that mental health treatment’s longer-term effectiveness is strongest among more financially advantaged probationers, consistent with this setting, in which the cost of mandated treatment is shouldered by offenders. Finally, conservative calculations result in a 5:1 benefit-to-cost ratio which suggests that the treatment-induced decrease in future crime would be more than sufficient to offset the costs of treatment. Chapter 2. Existing work has shown that the entry of a child into a household results in alarge and sustained increase in the earnings gap between male and female partners in oppositesex couples. Potential reasons for this include work-life preferences, comparative advantage over earnings, and gender norms. We expand this analysis of the child penalty to examine earnings of individuals in same-sex couples in the U.S. around the time their first child enters the household. Using linked survey and administrative data and event-study methodology, we confirm earlier work finding a child penalty for women in opposite-sex couples. We find this is true even when the female partner is the primary earner pre-parenthood, lending support to the importance of gender norms in opposite-sex couples. By contrast, in both female and male same-sex couples, earnings changes associated with child entry differ by the relative pre-parenthood earnings of the partners: secondary earners see an increase in earnings, while on average the earnings of primary and equal earners remain relatively constant. While this finding seems supportive of a norm related to equality within same-sex couples, transition analysis suggests a more complicated story. Chapter 3. Since 2001, more than half of US states have implemented policies that requireall public high schools to administer either the ACT or SAT to juniors during the school day free of charge, making that aspect of the college application process less costly in both time and money. I evaluate these policies using American Community Surveys (ACS) from 2000 to 2019. I augment ACS data with the Census Master Address File to precisely identify the state in which individuals took the exam. Exploiting variation in policy implementation across state and time, I find across all specifications that increased access to standardized college entrance exams has no effect on subsequent college attendance. It also does not shift students between public and private colleges or between two- and four-year programs. The results of this chapter suggest that, to the extent that these policies were introduced to encourage college-going among marginal students, they did not accomplish their goal. This provides evidence about the kinds of support necessary to influence educational outcomes for students from disadvantaged families.
Essays on Institutions, Governance and Economic Growth
(2024) Batra, Kartikeya; Galiani, Sebastian; Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
Economic development and growth are impacted by several factors. Among these, existing social institutions, and quality of governance are important determinants. These factors become especially relevant in the context of low and middle-income countries. Such nations are home to a large share of the world’s population, and aspire to grow their economies at high rates. Understanding constraints to their socio-economic development and prescribing policy solutions is, therefore, an important area of research. In the three chapters of this dissertation, I explore three different issues that impact social institutions and governance, which, in turn, impact socio-economic development. I do so in the context of India, which is home to approximately 20% of the world’s total population. In the first chapter, I explore whether historical land policies impact long-run socio-economic outcomes, including the persistent institution of the caste system and stereotypes associated with it. I find that lower land concentration does lead to improved socio-economic outcomes, especially for the socially marginalized landless communities. In the second chapter, I test whether enhanced state capacity by means of better public infrastructure improves the performance ofbureaucrats in rural India. I find that better roads lead to better bureaucratic performance, possibly due to improved monitoring by higher officials whose mobility is positively impacted. Finally, in the third chapter, I examine whether the size of a political party impacts its decisions to field wealthy candidates. I find that a smaller political party is likely to field a wealthier candidate than a bigger political party, possibly due to fewer avenues to mobilize resources. This is important, for the wealth profile of a candidate, in turn, has the potential to impact governance outcomes in their area. The three chapters are aimed at understanding causal relationships pertaining to important questions in the context of India’s society, political economy and economic development. My results provide novel contributions to relevant strands literature, and also allow me to provide relevant policy prescriptions.
ESSAYS ON CURRENCIES, CORPORATE BORROWING, AND INTERNATIONAL MACROECONOMICS
(2024) Lee, Seungeun; Kalemli-Ozcan, Sebnem; Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
This dissertation studies corporate real and financial decisions in responses to the global macroeconomic environment. In Chapter 1, I study the dynamic relation between dollar invoicing in exports, dollar borrowing, and the global financial cycle. I document a positive co-movement between dollar invoicing in exports and firms’ dollar borrowing, and also a positive link between dollar borrowing and the VIX. I write down a model consistent with these correlations: during global financial downturns when the VIX is high and dollar liquidity is tight, firms increase dollar invoicing to secure dollar revenues, facilitating dollar borrowing with these revenues as collateral. The model shows that an endogenous increase in dollar invoicing amplifies the responsiveness of dollar borrowing to positive global risk shocks (or safety shocks), affecting responses in variables like UIP premium, exchange rates, and foreign asset holdings. Empirical evidence from a comparison between Turkey and Thailand supports these insights. Chapter 2 presents both empirical and theoretical analyses about the effects of macroprudential policy measures (MPMs). I first examine the impacts of MPMs on the response of corporate loans to a U.S. monetary expansion, using panel data constructed from Dealscan database, IMF macroprudential policy index (MPI), and other macro variables. I find that MPMs attenuate the increase in corporate loans responding to a U.S. monetary expansion, but the effects are dampened as the country’s share of foreign loans goes up. This is because firms borrow more across borders with a decrease in the U.S. rate but MPMs cannot regulate the international borrowing. The introduction of capital flow management measures (CFMs) helps MPMs in managing corporate loans since they regulate capital inflows directly. My findings from a two- period model are consistent with the empirical evidence. I find that a special case of MPM, concentration limits, reduces the level and the growth of corporate loans when there is a decrease in the global interest rate. However, the effects of the MPM are dampened when firms are allowed to increase foreign borrowing, which can be resolved with the introduction of CFMs. An additional constraint imposed by a CFM sets a lower bound for a measure of the effectiveness of MPMs by limiting firms from borrowing overly from abroad.
ESSAYS ON DIGITAL ECONOMICS
(2024) Kim, Sueyoul; Jin, Ginger Z; Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
This dissertation studies economic questions in the digital environment. Specifically, it examines whether the design of a seller reward program on a livestreaming platform is optimal from the platform's revenue perspective, and how consumers' privacy concerns affect their behavior. In the first chapter, I present an empirical framework for assessing the impact of seller rewards programs on platform revenue. The context is a Korean livestreaming platform, where sellers (called streamers) broadcast content and receive tips from viewers to generate revenue. Platform revenue comes from commission charged on this revenue, and the reward is a permanent commission discount provided through performance-based monthly tournaments. I initially collect individual streamer-time level data, including efforts (measured by streaming hours), tipping revenue, and reward program acceptance. The collected data, along with anecdotal evidence, indicate that streamers exhibit heterogeneity in profitability, measured by tipping revenue per watch time. Furthermore, they tend to compete within specific broadcasting categories (e.g., within the Game category) to attract viewers. I then estimate a dynamic model to describe the effect of program design on streamers' behavior. The key trade-off for the livestreaming platform is that offering more commission discount rewards may increase the total tipping revenue by encouraging streamers---especially more profitable ones---to stream more, but it results in the platform taking a substantially smaller share of the generated tipping revenue. Counterfactual simulations reveal that the last platform share effect quantitatively dominates. This suggests that reducing the reward program by providing the reward to a smaller number of streamers or decreasing the commission discount rate would raise platform revenue. Additionally, these simulations identify opportunities to raise platform revenue by reallocating approval slots more granularly, at different broadcasting category levels instead of the entire platform level. In the second chapter, I empirically study how consumers' privacy concerns affect their behavior. Using panel survey data from South Korea that followed 5,328 individuals for four years, I find that privacy concern has a significant negative effect on their Facebook and Twitter usage. I additionally find that such concern has heterogeneous effects on online shopping behavior, while cloud storage services remain unaffected. When privacy-related events such as the Facebook-Cambridge Analytica data scandal in 2018 increases privacy concern, it appears to harm not only Facebook but also other firms in the industry (e.g., Twitter). Because a private firm does not internalize such negative spillovers, the privacy protection level determined in a free market could be different from the social optimum.
Essays on the Cognitive Foundations of Economics
(2024) Yegane, Ece; Masatlioglu, Yusufcan; Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
In Chapter 1, I model a decision maker who observes available alternatives according to a list and stochastically forgets some alternatives. Each time the decision maker observes an item in the list, she recalls previous alternatives with some probability, conditional on those alternatives being recalled until this point. The decision maker maximizes a preference relation over the set of alternatives she can recall. I show that if every available alternative is chosen with strictly positive probability, the preference order and the list order must coincide in any limited memory representation. Under the full support assumption, the preference ordering, the list ordering and the memory parameters are uniquely identified up to the ranking of the two least preferred alternatives. I provide conditions on observable choice probabilities that characterize the model under the full support assumption. I then apply our model to study the pricing problem of a monopolist who faces consumers with limited memory. I show that when the probability of forgetting is high, the monopolist is better off charging a lower price than the optimal price in the perfect memory case. In Chapter 2, Yusufcan Masatlioglu and I study how the allocation of attention to different options and the accessibility of options from memory affect decision making. To distinguish between attention and memory, we propose a two-stage stochastic consideration set formation process. An alternative enters the decision maker’s consideration set if it is investigated in the initial attention stage and is remembered in the subsequent recall stage. In the initial attention stage, the decision maker investigates each available alternative with some alternative-specific probability. In the recall stage, the decision maker recalls each alternative that she investigated in the attention stage with some probability. The probability of recalling an alternative depends on the memorability of the alternative and its position in the order of investigation in the attention stage. Investigating an alternative more recently enhances the probability of recalling it. The decision maker chooses the option that maximizes her preference relation over her consideration set. Under the assumption that the investigation of alternatives is observable, we provide testable implications on choice behavior and show that the revealed preference, attention parameters and memory parameters can be uniquely identified from observable repeated choices.
Essays on Information and Non-Bayesian Beliefs
(2024) Liu, Zhenxun; Filiz-Ozbay, Emel; Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
In this dissertation, I present a comprehensive discussion of a class of biases within the realm of probabilistic reasoning, namely confirmation bias (encompassing or closely related to commonly seen terms in the literature such as motivated reasoning and wishful thinking). The dissertation consists of three main chapters. In Chapter 1, I propose a new and improved belief updating model that can accommodate both motivated and unmotivated confirmation bias. The model improves upon existing models in its ability to explain data better, and its applicability to settings beyond binary-state spaces. I characterize the model with three intuitive axioms. In two extended applications, I show that the model establishes a link between confirmation bias and several well-known phenomena, such as the significance of first impressions, the polarization of beliefs, and the perseverance of inaccurate beliefs. In Chapter 2, I turn to the experimental elicitation of motivated and unmotivated confirmation bias. Previous experiments have provided evidence for motivated and unmotivated confirmation bias individually, but never discussed the possibility that the two can occur together in depth. This chapter presents one of the first experiments that examines both forms of confirmation bias together. Subjects were asked to update their beliefs regarding both politically contextualized questions and neutral questions. Subjects exhibited both motivated and unmotivated confirmation bias, but there was also significant heterogeneity among them. Notably, motivated confirmation bias is significantly stronger in later rounds of the experimental tasks, which may be correlated with the shorter response times in the later rounds. In Chapter 3, which is joint work with Emel Filiz-Ozbay, we discuss wishful thinking (motivated confirmation bias) within a major application. In a rational inattention setting where consumers acquire information on the good’s quality before making purchasing decisions, we examine the implications of the presence of consumers with wishful thinking. These biased consumers are unaware of their bias, and weigh any good news about the product quality more heavily than a Bayesian consumer. The firm, which aims to increase the volume of sales, can strategically constrain the accuracy of the information that consumers can acquire. We show that in the presence of biased consumers, a firm would find it profitable to constrain information acquisition unless the prior belief on the quality of the product is too low. We characterize the conditions under which the entry of a competitor firm can effectively alleviate this type of exploitation. Our findings shed light on the incentives of review platforms for bombarding wishful consumers with low quality product reviews and limit consumers’ ability to identify to reviews with informative contents.
ESSAYS ON ECONOMIC POLICY AND FIRM DYNAMICS
(2024) Kim, Seho; Aruoba, Boragan; Drechsel, Thomas; Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
This dissertation examines the impact of economic policies on aggregate economy by analyzing their effects on firms' behavior. It employs theoretical and quantitative macroeconomic models to explore how these policies affect social welfare. In Chapter 1, I study the second-best optimal carbon taxes when negative externalities from carbon emissions coexist with another inefficiency, specifically, the misallocation of production inputs across heterogeneous firms. This research holds relevance because governments may possess policy tools to address climate change, yet lack other means to alleviate additional inefficiencies. The motivation for this research stems from two prominent empirical facts. First, there is enormous heterogeneity in emission intensity across firms, even within narrowly defined 4-digit industries. Second, there is dispersion in the marginal products of production inputs, such as capital and labor, for firms within the industry, which is interpreted as evidence of misallocation of production inputs. Using a theoretical model, I show that when firms with lower emission intensity exhibit higher marginal products of production inputs, a carbon tax yields a double dividend: 1) it reduces carbon emissions; 2) it enhances allocative efficiency by reallocating resources to more distorted firms. Using firm-level data, I show that firms with lower emission intensity indeed have higher marginal products of capital and labor. Based on the empirical evidence, I develop a quantitative firm dynamics model that incorporates carbon emissions, emission externalities, adjustment costs, and financial frictions. In a calibrated version of this model, the optimal carbon tax is three times higher than in a counterfactual economy in which there is no relation between emission intensity and marginal products. Furthermore, I find that a policy directly targeting adjustment costs and financial frictions, if it exists, can simultaneously reduce carbon emissions and boost output, ultimately surpassing a carbon tax in increasing overall welfare. In Chapter 2 (co-authored with Thomas Drechsel), we explore the optimal macroprudential policy when firms face earnings-based borrowing constraints. Conventional wisdom in the literature suggests that when agents face asset-based collateral constraints—where the amount of debt is limited by the value of their asset holdings—they tend to over-borrow compared to the socially efficient level of debt. In this case, optimal policy aims to reduce debt positions through taxes. The reason is that agents do not internalize the effects of their debt choices on asset prices. However, recent empirical evidence shows that firms primarily borrow against their earnings rather than their assets. We show that agents over-save (and under-borrow) relative to the social optimum, as they do not internalize changes in wages, which in turn affect firms' earnings. This is the opposite conclusion to the previous literature. A numerical model exercise demonstrates that incorrectly rolling out a tax policy derived under the assumption of asset-based constraints in an economy where firms actually borrow based on earnings leads to a consumption equivalent welfare loss of up to 2.55\%. Thus, we argue that optimal macroprudential policy critically depends on the specific form of financial constraints. In Chapter 3, I investigate how the 2020 Small Business Reorganization Act, a corporate bankruptcy reform in the U.S. designed to reduce debt reorganization costs for small businesses, affects the aggregate economy. Under current U.S. law, businesses have two bankruptcy options: Chapter 7 liquidation and Chapter 11 reorganization. In Chapter 7, an insolvent company sells all of its assets, repays existing debts, and exits the market. In contrast, Chapter 11 is designed to rehabilitate efficient but financially distressed businesses. However, legal scholars have long argued that Chapter 11 is too costly for small businesses, causing productive but insolvent firms to choose liquidation, which could be potentially harmful to the economy. Using a general equilibrium model with bankruptcy decisions of firms, I evaluate the Small Business Reorganization Act. The main contribution to the literature is that I calibrate and estimate the model parameters using novel data encompassing the universe of bankrupt firms in the U.S., whereas existing literature primarily relies on data from bankrupt publicly listed large firms. I find that the bankruptcy reform has small but positive impact on aggregate welfare, while output and productivity decrease. A lower Chapter 11 cost helps distressed firms to reorganize, but also prompts firms that would not declare bankruptcy absent the reform to reorganize. Despite this unintended consequence, welfare of the economy improves.
ESSAYS ON THE ECONOMICS OF EDUCATION
(2024) Riquelme Gajardo, María Cristina; Urzúa, Sergio; Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
In this dissertation, I examine various factors shaping students’ trajectories and opportunitieslater in life. In Chapter 1, I explore the role of grade retention policies. Grade retention as a remedial policy is controversial because the benefits of extra instruction time may not outweigh its costs. Previous research has primarily examined retention for specific grades. By exploiting plausibly exogenous variation in retention generated by a nationwide promotion policy in Chile, I demonstrate that retention timing is critical in determining its effect on academic performance and access to higher education. Being held back only reduces the probability of future grade retention for young primary students. Additionally, older primary students are less likely to return to school the following academic year or graduate from high school. High school grade-retained students are the most affected, with a 10-20 percentage point reduction in their likelihood of high school graduation, and many switch to adult education in response to retention. Interestingly, even though high school students who are held back are just as likely to take the college admission test, they show a positive 0.1 SD increase in Spanish and math performance. Then, in Chapter 2, I focus on the impact of massive and sudden school closures followingthe 2011 nationwide student strike in Chile on teenage pregnancy. We observe an average increase of 2.7% in teenage pregnancies in response to temporary high school shutdowns, equal to 1.9 additional pregnancies per lost school day. The effect diminishes after three quarters since the strike’s onset. The effects are predominantly driven by first-time mothers aligned with highschool absenteeism periods and are unrelated to the typical seasonality of teenage fertility or pregnancies in other age groups. Additionally, we document that the strike had a larger disruptive role by affecting students’ educational trajectories, evidenced by a persistent increase in dropout rates and a reduction in college admission test take-up for both female and male students. Lastly, in Chapter 3, I explore inequalities in performance associated with the school typestudents attend, particularly the contribution of teachers to student performance in Chile’s college admission test (PSU). Our analysis is based on a unique teacher-student matched dataset and decomposition methods. The findings suggest that teachers’ performance on the PSU and the characteristics of their educational degrees are significant predictors of students’ success. When controlling for students’ and predetermined school characteristics, the gap between voucher and public schools reduces. Productivity differences emerge as key factors driving the disparities across school types. The analysis underscores the crucial role of teacher-student interactions in shaping student outcomes.
Essays on Production Networks and International Macroeconomics
(2024) Silva Uribe, Alvaro Nicolas; Kalemli-Ozcan, Sebnem S; Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
This dissertation includes three chapters on the role of production networks in (international) macroeconomics. In the first chapter, ``Inflation in Disaggregated Small Open Economies," I study the consequences of these production networks for our understanding of inflation in small open economies. I show that the production network alters the elasticity of the consumer price index (CPI) to changes in sectoral technology, factor prices, and import prices. Sectors can import and export directly but also indirectly through domestic intermediate input-output linkages. Indirect exporting dampens the inflationary pressure from domestic forces, such as adverse sectoral technology shocks and increases in factor prices. In contrast, indirect importing increases the inflation sensitivity to import price changes. Computing these CPI elasticities requires knowledge of the production network structure as these do not coincide with typical sufficient statistics used in the literature, such as sectoral sales-to-GDP ratios (Domar weights), factor shares, or imported consumption shares. Using input-output tables, I provide empirical evidence that adjusting CPI elasticities for indirect exports and imports matters quantitatively for small open economies. I then use the model to illustrate the importance of production networks during the recent COVID-19 inflation in Chile and the United Kingdom. In Chapter 2, ``Business Cycle Asymmetry and Input-Output Structure: The Role of Firm-to-Firm Networks" co-authored with Jorge Miranda-Pinto and Eric R. Young, we study the network origins of business cycle asymmetries using cross-country and administrative firm-level data. At the country level, we document that countries with a larger number of non-zero intersectoral linkages (denser networks) display a more negatively skewed cyclical component of output. At the firm level, firms with more suppliers and customers display a more negatively skewed distribution of their output growth. To rationalize these findings, we construct a multisector model with input-output linkages. We show that the relationship between output skewness and network density naturally arises once we consider non-linearities in production. In an economy with low production flexibility, denser production structures imply that relying on more inputs becomes a risk that further amplifies the effects of negative productivity shocks. On the contrary, when firms display high production flexibility, having more inputs to choose from becomes an opportunity to diversify the effects of negative productivity shocks. We calibrate the model using our rich firm-to-firm network Chilean data and show that (i) more connected firms experience larger declines in output in response to a COVID-19 shock, and (ii) the cross-sectional distribution of output growth in the model displays a fatter left tail during downturns. The previous result is shaped by the interplay between production complementarities and network interconnectedness rather than by the asymmetry of the shocks. The size of the shock determines the strength of the relationship between degrees and output decline, highlighting the importance of non-linearities and the limitations of local approximations. In Chapter 3, ``Commodity Prices and Production Networks in Small Open Economies" co-authored with Petre Caraiani, Jorge Miranda-Pinto, and Juan Olaya-Agudelo, we study the role of domestic production networks in the transmission of commodity price fluctuations in small open economies. We provide empirical evidence of strong propagation of commodity price changes to quantities produced in domestic sectors that supply intermediate inputs to commodity sectors (upstream propagation) and muted propagation to sectors using commodities as intermediate inputs (downstream propagation). We develop a small open economy production network model to explain these transmission patterns. We show that the domestic production network is crucial for shaping the propagation of commodity prices. The two key mechanisms that rationalize the evidence are (i) the foreign demand channel and (ii) the input-output substitution channel. These two channels amplify the upstream propagation of commodity price changes by increasing the demand for non-commodity inputs, and, at the same time, they mitigate the downstream cost channel by allowing firms to use relatively cheaper primary inputs in production.
Essays on Competition and Innovation
(2024) Leccese, Mario; Jin, Ginger Zhe; Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
The relationship between product market competition and corporate innovation is shaped by a complex interplay of market forces, regulatory environments, and technological trends. The study of young ventures has long been deemed essential in understanding technological progress and the phenomenon of creative disruption. Over the past few decades, venture capitalists (VCs) have played a pivotal role in fostering the growth of startups, particularly within the technology sector, by screening and advising them to successfully bring innovative products or services to the market. Thus, understanding how competition among startups affects VCs’ investment decisions and guidance is vital for comprehending the pathway to startup success and the dissemination of their innovative ideas into the market. In the first chapter of this dissertation, I examine the effect of VCs’ strategic investment in potentially competing startups on those startups’ outcomes. Using a new analytical framework, I highlight two effects. First, VCs internalize the competition among portfolio startups, and this impacts their incentives to engage in activities that influence startups' outcomes. Second, by investing in a business area, VCs learn to select better startups within that business area. This selection effect incentivizes VCs with competing portfolio startups to take actions enhancing the outcomes of their subsequent investments at the expense of the first one. To test the hypotheses, I combine venture investment data from Crunchbase (2008-2021) with S&P 451 Research, a tech M&A database that classifies startups according to a unique hierarchical technology taxonomy. I find that the first of the competing startups invested by a VC exhibits poorer performance after the VC invests in a competitor, as compared to startups that do not share any VC with a competitor. In contrast, subsequent startups invested by the VC in the same business area outperform startups not sharing a VC with a competitor. While these results are partly attributable to the selection effect, they also indicate that investing in competitors enables VCs to exert additional influence on their portfolio startups, favoring subsequent investments over initial ones. My findings contribute to a broader literature on innovation by documenting how externalities between startups in the portfolio of the same investor interact with portfolio value maximization strategies and affect both entrepreneurs and investors. Chapter 1 underscores the influence of competition dynamics on the trajectory of startup-driven innovation and its eventual accessibility to consumers on the market. However, when successful startups enter markets and compete with established incumbents, their innovations can disrupt the competitive landscape. For example, ride-sharing companies like Uber and Lyft, backed by VCs, introduced a new business model relying on superior technology to match drivers to riders and transformed a heavily regulated industry like the taxi one. Thus, the second part of the dissertation shifts focus to the competition between innovative entrant platforms and regulated incumbents, using the taxi industry as a case-study. While the emergence of ride-sharing platforms brought significant benefits to consumers through enhanced matching technology, it also led to the devaluation of taxi licenses, posing challenges for policymakers. Despite taxes levied exclusively on platforms are arguably among the main tools on the agenda, relatively few papers have studied their effects. Chapter 2 fills this gap by analyzing the effects of a tax imposed by the city of Chicago, which levied taxes on ride-sharing but not traditional taxi trips. I document a significant increase in ride-sharing prices, particularly for single rides starting or ending in downtown Chicago, which faced the largest tax increment. Tax pass-through rates were approximately 100% for single rides and even more pronounced for shared rides in the downtown area. This pattern can be explained by the fact that ride-sharing companies are multi-product peer-to-peer platforms and riders may substitute single with shared rides. The tax steered riders towards shared options downtown, leading to a slight increase in traditional taxi usage. Conversely, areas outside downtown witnessed reduced ride-sharing use, with no rise in demand for taxis. This is consistent with a more intense competition between taxi and ride-sharing services downtown. Lastly, although the tax alleviated congestion, the magnitude of this benefit remains modest and constrained to the downtown area. By introducing a new technology and competing with traditional taxis, ride-sharing companies not only ensure lower prices and higher quality of service to riders but also help reduce inequality in their access to transportation means. In effect, the ability to commute affordably and reliably across neighborhoods can facilitate socio-economic and racial integration and reduce spatial mismatches. This suggests that taxes such as the one analyzed in Chapter 2 can also exacerbate disparities across different groups of the population by unequally affecting urban mobility, thus generating significant distributional costs. In Chapter 3 I examine the heterogeneous impact of the same tax across different community areas in Chicago, focusing on whether it had unequal consequences in community areas with different racial compositions. I document significant heterogeneity in price increases due to the tax across the community area of departure as well as across destination points, providing evidence that this was correlated with community areas’ differential access to alternatives to ride-sharing, such as public transit. Clustering community areas based on racial composition reveals that Black areas experienced the highest price increases and percentage reductions in ride-sharing usage. Overall, the losses in rider surplus were larger in minority-concentrated areas. These findings highlight the potential trade-offs between addressing negative externalities and exacerbating inequalities in urban policy and suggest the need for further research on the impact of congestion policies on racial inequality.
ESSAYS ON THE ECONOMICS OF GOVERNMENT REGULATION
(2024) Zhou, Qiyao; Jin, Ginger; Galiani, Sebastian; Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
Government regulations play an increasingly important role in shaping economic activities across the world. This dissertation consists of three chapters that explore the efficacy and efficiency of government regulations in the context of developing economies. The first chapter studies the welfare impact of price ceiling on the new house market in Shanghai. The second chapter studies the optimal design of the recurring auctions and its applications in the home foreclosure auction market. The third chapter studies the optimal design of the presale policy in the residential housing market in China. Chapter 1. Under Control? Price Ceiling, Queuing, and Misallocation: Evidence from the Housing Market in China The first chapter develops a model to study the equilibrium effects of price control policies. The framework considers the option for consumers to wait and re-enter the market if items are not immediately allocated due to excess demand. While waiting is commonly associated with the price ceilings, the cost of waiting has received limited attention in prior research. In this chapter, I focus on the housing market in Shanghai, where a price ceiling has been imposed on new houses since 2017, while the existing houses are not regulated. Using a structural model, I estimate household demand, housing supply, and waiting costs. The price ceiling on new houses resulted in a social welfare loss of 13 billion USD from 2018 to 2020. Consumer surplus increased by 1.3 billion USD, as most of the gains from lower prices of new houses were offset by waiting costs and misallocation. Counterfactual analyses suggest that distributing a discount voucher to buyers rather than imposing a price ceiling could significantly reduce the welfare loss and achieve more equitable outcomes. Chapter 2. Recurring Auctions with Costly Entry: Theory and Evidence, (with Shanglyu Deng) Recurring auctions are ubiquitous for selling durable assets like artworks and homes, with follow-up auctions held for unsold items. The second chapter investigates such auctions theoretically and empirically. Theoretical analysis demonstrates that recurring auctions outperform single-round auctions when buyers face entry costs, enhancing efficiency and revenue due to sorted entry of potential buyers. Optimal reserve price sequences are characterized. Empirical findings from home foreclosure auctions in China reveal significant annual gains in efficiency (3.40 billion USD, 16.60%) and revenue (2.97 billion USD, 15.92%) using recurring auctions compared to single-round auctions. Implementing optimal reserve prices can further improve efficiency (3.35%) and revenue (3.06%). Chapter 3. Haste or Waste? The Role of Presale in Residential Housing (with Ziyang Chen, Maggie Hu, and Ginger Jin) The third chapter provides the first theory and evidence on the role of presale policies in the residential housing market. This chapter starts with constructing a novel dataset of unfinished projects, presale policies, and land auction outcomes across 270 major cities in China. 2,330 unfinished residential projects are identified from 2010 to 2017 on a citizen complaint website run by the central government. We find that both presale criterion and postsale supervision of construction costs relate to a lower probability of unfinished projects. But only presale criterion relates negatively to the pace of new housing development, measured by developers' multitasking and land auction outcomes. A back-of-the-envelope calculation suggests that the average bundle of presale policies is inferior to the Pareto frontier in our sampled cities. Tightening the regulation on postsale supervision by 2 standard deviations may lead to a 58\% reduction in the occurrence of unfinished projects while keeping the pace of new housing development unchanged.
An Empirical Analysis of the Determinants of Initial Occupational Choice by Male High School Graduates
(1986) Cox, Donald Francis; Brechling, Frank; Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, MD)
This dissertation consisted of an empirical analysis of the determinants or initial occupational choice by male high school graduates. The approach used was based on the theory of random utility. According to this approach, the individual selects a particular outcome from a set of possible outcomes based on both observed and unobserved characteristics of the individual and the particular possible outcome. In this analysis, the occupational choice set contained three possible outcomes. These possibilities were civilian sector employment, military service and college enrollment. For empirical analysis, a sample of 1,748 male high school graduates was drawn from the National Longitudinal Survey of Youths (1979-1981). The empirical model consisted of a mixed discrete/continuous simultaneous 4 equation system. Three estimation strategies were used. The first was a sample two stage logit/ordinary least squares procedure. The second was a modified two stage logit/ordinary least squares procedure that corrected for self-selectivity bias. the third strategy consisted of a modified two stage logit/ordinary least squares procedure that corrected for both self-selectivity and choice-based sampling bias. The estimation results indicate that the decision to enlist is most sensitive to the net income of the individual's family and the predicted civilian sector wage. The military experience of the individual's father and the desire to acquire additional training are also important in this decision. In addition, the differences in the estimates across the three estimation procedures illustrate the importance of correcting for sample biases.
Essays in the Economics of Immigration
(2023) Soriano, John Joseph Sanchez; Hellerstein, Judith K; Pope, Nolan G; Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
Chapter 1 sets the stage for Chapters 2 and 3, which involves the empirical analyses of the effects of two prominent immigration policies: Deferred Action for Childhood Arrivals (DACA) and the Immigration Reform and Control Act (IRCA). This chapter begins with a review of the history of modern US immigration policy and relevant empirical evidence regarding it. It then focuses on three special topics: immigration and labor markets, immigration and crime, and the effects of enforcement policy. These topics are chosen for their contextual relevance for DACA and IRCA, as well as for marriage. Chapter 2 examines the impact of Deferred Action on Childhood Arrivals (DACA) on the marriage outcomes of its recipients. DACA, an immigration policy introduced by President Barack Obama in 2012, provides temporary benefits to unauthorized immigrants who arrived in the US as children. By analyzing data from the American Community Survey (ACS), the study examines the effects of DACA eligibility on the probability of being married and the types of individuals DACA recipients marry. The findings suggest that DACA eligibility increased the likelihood of marriage by approximately 2 percentage points, with deportation relief being a key driver for women and work authorization playing a more prominent role for men. The analysis also reveals that DACA recipients are more inclined to marry US natives, emphasizing the desire for assimilation, and tend to choose spouses who are fluent in English, indicating the influence of DACA on language-related assimilation. Chapter 3 investigates the impact of the legalization provision of the Immigration Reform and Control Act of 1986 (IRCA) on marriage rates. The IRCA offered a pathway to citizenship for unauthorized immigrants. Using data on unauthorized immigrants that were legalized under the IRCA from the Legalized Population Survey (LPS) and a comparison group of US natives from the National Longitudinal Survey of Youth (NLSY79), the study implements an individual fixed effects strategy to estimate the changes in marriage rates as a result of the IRCA legalization. The findings reveal a statistically and economically significant increase in marriage rates for both men and women following IRCA legalization. Men experienced a 6.51 percentage point increase, while women saw an 8.29 percentage point increase. Unlike the effects observed in Chapter 2 for DACA, the permanent nature of the IRCA contributed to a stronger impact on marriage rates. The study explores potential mechanisms but finds inconclusive evidence regarding labor market outcomes and education as drivers of the marriage effect resulting from immigration liberalization.
On Terrorist Attacks and Estimation Methods
(2023) Macario, Pablo; Prucha, Ingmar R; Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
In my thesis I propose a theoretical model of terrorist attacks and anestimation strategy which I compare to existing methods in the literature. The modeling approach was designed with terrorism in mind, but can be applied to other discrete dynamic decision processes with a latent component and a random payoff variable that is measured when the agent exits a state of waiting. Chapter 1 briefly describes the structure of the thesis. Chapter 2 provides a literature review of empirical studies of terrorist attacks. The primary focus is the series hazard model that estimates the effect of policy interventions on the risk of terrorist attacks. Recent contributions include LaFree et al. (2009), Dugan (2011), Carson (2014) Argomaniz and Vidal-Diez (2015), and Carson (2017). A major limitation of the series hazard approach is that it is unable to evaluate the impact of a policy intervention on the outcomes of attacks (e.g., the number of fatalities) even if these are measured during each event. Chapter 3 introduces the sequence hazard model of a terrorist groupdeciding when to attack. The model links the outcome of terrorist attacks to the choice of when to attack by taking the amount of time elapsed since the last attack as an input into the planning of the next attack. The agent trades off the desire to improve their attack against the risk that their plans are sabotaged before they are able to carry them out. The sequence hazard model is dynamic because agents take into account the potential size of future attacks when deciding whether or not to attack today. As a consequence, the hazard implied by the sequence approach is non-proportional in time. This distinguishes the sequence hazard model from the proportional hazard assumed by the series (Cox) approach. The sequence model implies a data generating process for attack outcomes that takes into accountthe probability the agent attacks. Chapter 3 derives the implied mathematical expectation and variance of attack outcomes which allows researchers to extend the notion of deterrence to allow for the possibility that counterterrorist policies that reduce the frequency of attacks, but increase the expected severity of attacks that do take place. Two types of attack outcomes are considered, a mixed Poisson-beta model for the number of casualties and a mixed Bernoulli-beta model for attack success or failure. Chapter 4 presents a Monte Carlo study demonstrating the validity ofestimating the sequence hazard model by maximum likelihood. In contrast, when the underlying data are generated according to the simple behavioral model presented in Chapter 3, the series hazard fails to estimate the true effect of a policy intervention on the risk of attacks. Moreover, the standard tests fail to reject the null hypothesis that the data are generated according to a proportional model. The simulation implies that if planning time and uncertainty over attack outcomes are important elements in terrorist decision making, then methods of policy evaluation based on the assumption of proportionality may not be appropriate. In contrast, by modeling both the timing of attacks as well as their size, the sequence hazard offers a straightforward way of incorporating terrorist attack outcomes into the analysis of counterterrorism policy.

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