Economics Theses and Dissertations

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    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.
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    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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    Essays on the Economics of Crime, Gender, and Health
    (2023) Ramirez Pierce, Elena; Goldberg, Jessica; Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    In this dissertation I study the impacts of large government programs on crime and health outcomes. I also run an online experiment about the use of professional titles to elicit perceptions of experts cited in major news outlets and to test whether these perceptions vary across genders. In the first chapter, I examine the effects of large changes in cash availability on crime. South Africa has a large social safety net comprised of numerous cash transfer programs, called social grants, that are paid on a monthly basis. Prior to late 2018, these social grants were paid mostly in cash at grant disbursement locations called paypoints. Using a differences-in-differences (DiD) strategy, I analyze the effects of the temporary increase in cash availability on crime by comparing crimes on social grant payment dates in small geographical areas, police precincts, between areas with differing numbers of cash disbursement locations. The results suggest a small decrease in crime the day prior to social grant payments, and small increases the day of payments or the day after payments, depending on the empirical specification. These results are consistent with perpetrators potentially delaying their labor supply of crime until the widely publicized cash grant payment days, an anticipation effect, and increasing their labor supply of crime on or after payment days consistent with a loot effect, resulting from increased cash and purchased goods availability. Chapter two investigates whether there exists a credibility penalty for female experts compared to male experts when major news outlets forgo the use of professional titles, such as ``Dr." that serve as an information signal on the level of their training. Given the extensive literature on gender and racial bias in media reporting and professional and academic environments, the practice of abstaining from the use of professional titles may reinforce and even exacerbate these biases. In this co-authored analysis, we test for differential effects by conducting an online experiment that presented survey respondents with news articles holding constant content, but varying the gender and title of the cited experts and asked them to rate the expert's credibility. Our design enables between-subject and within-subject analysis. While we are able to detect a positive credibility effect of using professional titles, we are unable to distinguish a differential credibility impact across gender. Finally, in chapter three I estimate the effects of a large-scale national physician provision program in Brazil on birth outcomes. Given the risk to mothers of injury and disease associated with childbirth that may affect the health of the newborn, as well as the myriad of complications that may arise that could threaten the health of the fetus, increasing access to and quality of medical care may have substantial effects on birth outcomes. The Mais Medicos Program (PMM) focused on equalizing physicians per capita as well as generally increasing the number of physicians across the country. Beginning in late 2013 and an executive branch initiative, the program placed almost 20,000 physicians by 2016, predominantly from Cuba, throughout the country. Using vital statistics data of the universe of births in Brazil from 2006 to 2017, I estimate the effect of increasing the supply of primary care physicians on birth weight using both a differences-in-differences and an instrumental variables approach. I find that PMM resulted in higher average birth weight for children throughout Brazil. However, I find no improvement on the incidence of low birth weight or any weight effects for those living in rural parts of the country. Hence, these results imply PMM did not affect the most vulnerable pregnancies.
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    Three Essays About Economic and Behavioral Responses to Government Interventions
    (2023) Chatterjee, Mrinmoyee; Hellerstein, Judith K; Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    This dissertation studies three different policy interventions and the subsequent labor marketresponses across different times and contexts. In Chapter 1, I study changes in the relative wages for women in manufacturing between 1940 and 1950. World War II saw an unprecedented influx of women onto factory floors. While most previous literature focuses on the effects on female labor supply via geographical variation in military mobilization, Rose (2018) highlights the importance of production demand in driving female wartime employment. Using data on the wartime employment of women from Rose (2018), I revisit the framework in Acemoglu et al. (2004), and estimate the impact on relative wages for women, due to both state-wide and industry-wide changes in production demand during WWII. I find that wages increased for women in 1950 compared to 1940 in Durable Manufacturing by 35.4-35.9% in the industry with the largest change in the relative demand for women during WWII, whereas impacts of state-level changes in demand are not significant. Impacts on wages in Non-Durable Manufacturing are statistically insignificant. The relative wage gains are highest for women with 12 or more years of education, suggesting that the increased demand during WWII allowed some women a “foot in the door” into prized manufacturing jobs. My work helps to reconcile the prior literature connecting WWII to gains in employment for women, and recent work highlighting the importance of the War Production Effort in increasing female employment, by showing how changes in the relative industrial demand for women during World War II significantly increased relative wages for women. In addition, by focusing my analysis on Manufacturing industries, (which saw the largest changes in wartime demand), I consider finer industry variation nationally than any previous work in this context. In Chapter 2, (co-authored with Dheeraj Chaudhary), we test if the intra-state deregulation of banks between 1970–2000 had any impacts on fertility rates. U.S. states deregulated their banking sectors in a staggered fashion between 1960-1999, increasing efficiency through competition between banks and boosting economic growth within a state. We find that deregulated states saw a decrease of approximately 4–6% in their average fertility rates (in both state-level as well as individual-level data) using a classic difference-in-differences strategy leveraging the staggered timing of deregulation across states. In updating our results with recent econometric literature to account for differences in treatment timing, we find that our results are robust for the sample of observations before 1989 but not for later years. Women aged 20-44 saw a decrease of approximately 2-3% on average fertility rates post-deregulation (in both state-level and individual-level data) between 1970 and 1988. We test different possible mechanisms and find that a likely mechanism could be the increased opportunity costs of having children in a growing job market for women, especially in non-white and poorer households. In my third and final chapter, (co-authored with Nolan Pope), we look at the academic impacts of a recent large-scale AC installation program in Chicago Public Schools. Since growing evidence demonstrates that heat impairs student learning, a potential policy solution is clearly investing in air-conditioning. Making use of the timing of roll-out of AC across schools, in a $135 million AC installation program undertaken by Chicago Public Schools between 2013–2017, we analyze the effects on student outcomes. We find no evidence AC installation improved students’ end-of-year test scores or grade retention, and find marginal improvements in attendance. These results indicate that improvements in test scores (or other student outcomes) with AC installation could be region-dependent with the impacts of heat on learning, and considering the returns can help school districts better optimize their often limited budgets when striving to improve student performance.
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    Essays on Information Frictions and Macroeconomic Uncertainty
    (2023) Hong, Zu Yao; Stevens, Luminita; Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    This dissertation studies the role of information frictions and uncertainty in the macroeconomy. The three chapters expand a basic environment with information frictions to feature (i) variable information quality, (ii) tail risk, and (iii) social learning. The first chapter introduces information quality in a real business cycle model with costly information. Using data from the Survey of Professional Forecasters, I document that forecast errors are larger during downturns, even though agents acquire more information. I then augment a rational inattention model with variable information quality. Information quality depends on both data abundance and search intensity in the demand for information. Unlike rational inattention models, in which there is perfect supply of information, I allow for time-varying data abundance, or information supply. Procyclical supply of information generates pro-cyclical information quality, which in turn rationalizes the puzzling evidence that information acquisition and uncertainty both increase in downturns. A Bayesian estimation of the model for the U.S. economy shows that information quality accounts for sizable fluctuations in uncertainty and aggregate output. The model also generates: (i) systematic biases, if agents do not take into account fluctuations in information quality, (ii) variation in information processing costs, which produces dispersion in downturns, and (iii) production externalities, as firms do not internalize that more activity generates data abundance, which reduces uncertainty. The second chapter (co-authored with Yeow Hwee Chua) studies expectations formation in a Bayesian learning framework when the environment features tail risk. First, in the presence of tail risk, second moment shocks lead to more pessimistic forecasts compared with the forecasts generated in an environment that has zero probability of tail risk events. Second, individuals overreact to first moment shocks compared to the environment without tail risk, as they reassess the probability of finding themselves in a disaster state. Third, the magnitude of the overreaction depends on the level of uncertainty. We document these theoretical predictions for the U.S. economy over the 1978 to 2016 period, using data on expectations, uncertainty, sentiment, and tail risk. The theoretical framework predicts that not accounting for tail risk would lead the econometrician to conclude expectations are biased even though agents are in fact fully Bayesian. The third chapter studies uncertainty contagion across countries in a model of endogenous information acquisition with social learning. Motivated by evidence that macroeconomic uncertainty tends to comove across countries, this chapter builds a two-country model of rationally inattentive decision-making in which each country learns about national and international conditions independently and from each other. When fundamental uncertainty exogenously rises in one country, economic agents in that country allocate more attention to local conditions and less attention to international conditions. Global uncertainty rises as a result, and agents in the other country endogenously reallocate more attention to global conditions. This results in an increase in uncertainty about idiosyncratic conditions in the other country, even though there has been no change in fundamental uncertainty in that country. The model also predicts higher uncertainty contagion during crises.