Theses and Dissertations from UMD
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Item Unawareness, and its Effect on Beliefs, Learning, and Group Decision Making(2024) Tashiro, Masayuki; Pacuit, Eric; Philosophy; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This dissertation consists of three standalone papers centered around the concept of unawareness. The first paper, titled `Weak Explicit Beliefs', concerns the effect of unawareness to one's beliefs and extends the standard logic framework of awareness with a novel notion of beliefs under unawareness. The second paper, titled `Learning under Unawareness' concerns the effect of unawareness in one's learning process and extends the standard logic framework of awareness with two dynamic modal operators: learning and change of awareness. Lastly, the third paper, titled `Models of Group Deliberation with Asymmetric Awareness' concerns the effect of unawareness in group decision making situations, in which each agent in the group may be un/aware of different things, and explores a normative question whether it is always better to become more aware (of what the other agents in the group are aware of) via two formal models of group deliberation.Item The Language of Central Banking: Probing Global Monetary Policy Communications Spillovers and Central Bank Shocks with Natural Language Processing Tools and a Novel Text Database(2024) Baird, Cory; Swagel, Phillip; Public Policy; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The discipline of macroeconomics relies mainly on structured data for empirical research, despite unstructured text data being vastly more abundant. This text data, particularly central bank communications, holds untapped potential for monetary economics research due to their influence on market expectations and policy outcomes like inflation. To help guide monetary policy researchers in exploring the growing universe of text data, this research lays out a foundational framework, both in terms of coding infrastructure and Natural Language Processing (NLP) methods. The first step in building out this infrastructure is through the creation of a new open-source central bank text database consisting of monetary policy communications from 14 countries consisting of 2,418 monetary policy statements. I leverage this novel database to explore the literature on "information effects," which has mainly relied on structured data for empirical analysis despite the possibility that the phenomenon itself is attributable to the linguistic elements or sentiment expressed via central bank communications. Chapter 1 (The Anatomy of a Central Bank Statement and Information Shocks) details the steps necessary to create a reproducible and scalable database of monetary policy statements from a diverse group of countries using the latest open source technologies and modern data science practices. I find that positive co-movement between policy rates and equities (what the literature defines as an "information shock") is a common event, with almost half of all policy rate increases (decreases) occurring alongside higher (lower) equity prices. With linguistic regressions and part-of-speech annotations, I provide novel linguistic evidence that information shocks are likely related to both the future state of the economy \parencite{nakamura2018high} and inflation expectations \parencite{boehm2021beyond}. Chapter 2 (Sentiment Analysis-From Past to Present) develops a novel approach for extracting sentiment at the sentence level using cutting-edge transformers models, the architecture behind many large language models (LLMs). My research demonstrates that transformer models as well as the traditional lexical methods employed in the economic literature, can produce starkly divergent results when applied to the same monetary policy statement. This highlights the critical need to utilize multiple sentiment measures to ensure the robustness of any findings derived from textual analysis. Reinforcing the linguistic evidence from Chapter 1, I show that positive (negative) sentiment is associated with positive (negative) information shocks providing further evidence the shocks are driven by the language of the statement itself. I also show that positive sentiment is associated with higher GDP growth in the quarters following a monetary policy statement. Chapter 3 (Central Bank Shocks and Global Spillovers), aggregates sentiment measures from the previous chapter to produce what I call the Global Policy Stance (GPS). I find that the GPS, led by the U.S., Japan, and Switzerland, tends to co-move with the global financial cycle (Global Asset Prices Factor from \textcite{miranda2020global}). I also find that domestic sentiment, rather than U.S. or global sentiment, is predictive of future policy rate changes suggesting that markets may be more sensitive to the communications of the home country's central bank. This thesis sets a rigorous standard for database transparency and code reproducibility above and beyond what is standard practice in the economics literature today. I will publicly release the codebase encompassing data retrieval, cleaning processes, figure generation, model development, all of which were produced utilizing the open-source Python programming language. Through this public release, I will provide researchers with valuable coding infrastructure that supports the operationalization of best practices in data management, enabling (1) the creation of open-source databases fostering collaboration and automation, as well as (2) the development of reproducible, scalable algorithms for text classification and text cleaning processes. In the future, I intend to further build out the central bank database to include other types of monetary policy communications (e.g., minutes and speeches) while also separately maintaining a repository of text classification algorithms (e.g. positive and negative sentiment) including lexical dictionaries from the literature as well as fine-tuned transformer models.Item 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.Item Increasing Charitable Giving Using Subsidies: Theory and Experiments(2024) Higgs, Zed; Uler, Neslihan; Agricultural and Resource Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This dissertation combines theoretical analysis with economic experiments to advance our understanding of why people give. In particular, this dissertation focuses on the use of subsidies for giving---e.g., rebates and matches---as a tool for increasing charitable giving. The research included in this dissertation provides important guidance to charitable organizations seeking to design fundraisers optimally to maximize charitable receipts. Furthermore, this research also provides important guidance to policy-makers seeking to better understand the interplay between tax policy and charitable giving. The results of this dissertation can contribute to more effective fundraising campaigns and more efficient tax policy. Chapter 1 challenges the well-established result among existing experimental studies that donations are significantly more responsive to matches than to rebates. In previous experimental studies the budget sets available to subjects under rebates are constrained relative to those available under matches, biasing estimates of the rebate-price elasticity. We conduct a novel experiment that removes the constraint under rebates, producing equal budget sets for price-equivalent rebates and matches. Contrary to previous studies, we find dramatically smaller differences in donations under price-equivalent matches and rebates. More importantly, we find no statistical difference between our estimated rebate- and match-price elasticities. Furthermore, we show that the constraint under rebates affects the entire distribution of observed behavior, not only the behavior of individuals for whom the constraint is binding. This chapter contributes to theories of charitable giving and has important implications for tax policy. Chapter 2 studies how donor uncertainty affects their response to match subsidies in the context of charitable giving. It explores whether donors are responsive to exogenous changes in the probability of receiving a match. I develop a theoretical model of giving that incorporates uncertainty around matches. I demonstrate the model is capable of explaining the discrepancies in match-price elasticities of giving observed across previous field experiments and observational studies. I then derive testable hypotheses from the model, and design and run an economic experiment to test these hypotheses. The results of my experiment provide clear evidence that donors are responsive to changes in the probability of receiving a match. As a result, the same donor may respond differently to match subsidies depending on the setting. This work identifies an important aspect of donor decision making, contributing to a better understanding of why people give. It has important implications for theories of giving, the optimal design of fundraisers, and tax policy. Chapter 3 builds on Chapter 2 to continue studying how donor uncertainty affects their response to match subsidies in the context of charitable giving. It explores whether donors are responsive to endogenous changes in the probability of receiving a match resulting from changes in fundraiser characteristics. The results provide strong evidence supporting the notion that changes in fundraiser characteristics can affect donors' beliefs about the probability of receiving a match, in turn affecting their donation decisions and the observed response to match subsidies. The effectiveness of a match subsidy varies depending on the characteristics of the fundraiser, so that the optimal fundraising strategy varies across fundraisers. This chapter provides new guidance for fundraisers interested in increasing charitable donations through the use of match subsidies.Item ESSAYS ON THE DESIGN AND EVALUATION OF PAYMENTS FOR ECOSYSTEM SERVICES PROGRAMS(2024) Kim, Youngho; Lichtenberg, Erik; Newburn, David; Agricultural and Resource Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Nature-based solutions for climate change mitigation and adaptation emphasize the restoration of natural infrastructure and the adoption of conservation practices in agriculture. Payment for ecosystem services (PES) programs play a key role in these efforts by offering financial incentives to farmers and landowners who adopt land use or management activities that provide environmental amenities and services for society. This dissertation consists of three chapters that examine the optimal design of PES programs and evaluate their performance in the context of climate change and environmental protection. The first chapter investigates whether PES programs contribute to climate change adaptation by reducing economic losses from extreme weather events. I evaluate the cost-effectiveness of the Conservation Reserve Enhancement Program (CREP) in the United States in mitigating flooded crop losses through the restoration of riparian buffers and wetlands. By leveraging variation in the timing of program introduction across counties in the Mississippi River Basin, I find that the introduction of CREP reduced both the number of flooded acres and the extent of damage on those acres. CREP also generated financial spillover effects on the federal crop insurance program, reducing indemnity payouts that would have otherwise been allocated to insured farmers. This study enhances our understanding of how PES programs promote sustainable agriculture and facilitate nature-based solutions for climate change adaptation. The second chapter examines the cost-effective structure of payments and penalties in PES programs, in collaboration with Erik Lichtenberg and David Newburn. The sustainability of ecosystem services programs is contingent on landowners’ compliance with the signed contracts after their initial participation. However, premature contract terminations are not uncommon, particularly when unexpected increases in crop prices lead to the removal of established conservation cover on agricultural land. In such cases, PES programs typically require participants to repay all payments received up to the date of contract termination (e.g., those in the US, the EU, Costa Rica, Mexico, Australia, and many other countries). This standard penalty structure is inefficient because it directly couples penalties with payments, increasing monotonically during the contract period. This study is the first to derive the optimal penalty structure that equals net environmental benefits for the remaining contract period, which decouples penalties from payments. A numerical policy simulation using integrated assessment models shows that the U.S. federal PES programs can substantially increase the environmental benefits by restructuring the current standard penalty. Importantly, the optimal penalty tends to decrease gradually during the contract period, providing credit to farmers for the ecosystem services generated prior to the contract termination. This finding has broad implications for restructuring PES programs in the U.S. and globally, and the study has been published in the Journal of Environmental Economics and Management. The third chapter examines the influence of U.S. federal agricultural conservation programs on the performance of emissions trading programs in promoting afforestation activities on agricultural land, in collaboration with Erik Lichtenberg, David Newburn, Haoluan Wang, and Derek Wietelman. Emissions trading programs, which pay for performance, have been advocated as flexible and efficient tools for achieving pollution reduction goals when evaluated in isolation. However, these programs often operate within a policy landscape dominated by conservation subsidy programs that pay for effort. We find that current federal conservation subsidies are so generous that they significantly crowd out water trading programs when both are in competition, although water trading programs would be effective in isolation. In addition, current carbon market payments for offsets are insufficient to make emissions trading programs more attractive compared to longstanding agricultural conservation subsidy programs. While prior studies have attributed low farmer participation in emissions trading programs to transaction costs and market uncertainty, our analysis suggests that even if these impediments are removed, competition with existing pay-for-effort programs would remain a significant barrier to expansion of emissions trading among agricultural producers. Therefore, the attractiveness and effectiveness of emissions trading programs for afforestation depend heavily on the presence and generosity of longstanding federal agricultural conservation subsidies.Item The Economics of Spruce Budworm Monitoring and Management in Eastern Canada(2024) Holm Perrault, Alexandre Ismaël Eliot; Olson, Lars J; Agricultural and Resource Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This dissertation uses techniques that were developed for renewable natural resource and invasive pest management to describe the two principal challenges of eastern spruce budworm (SBW) monitoring and management in Eastern Canada, with a specific focus on the province of Quebec. The primary empirical components of this dissertation can be found in Chapters 2 and 3. Chapter 1 provides the necessary historic, entomological, ecological and policy context to understand Chapters 2 and 3. Chapter 4 provides a conclusion to this dissertation by proposing extensions that would make the models presented in Chapters 2 and 3 more readily applicable to real-world spruce budworm management. These extensions involve making the models spatially explicit, as the models presented in Chapters 2 and 3 are spatially crude for the sake of tractability. Chapter 2 describes the management of an endemic irruptive forest pest and, using the spruce budworm-balsam fir forest interaction, proposes an optimization model that determines optimal pest treatment and forest harvest levels for a single, dimensionless forest stand that is currently undergoing an active budworm outbreak. Budworms cause both growth reductions and mortality on the forest biomass stock, and increasing forest biomass will provide budworms with more prey, causing their growth rate to increase. Treatment decisions are limited to three discrete possibilities (0, 1 or 2 on the landscape) that impose mortality on budworms, while harvests remove a proportion of the forest biomass. Using a numerical solution algorithm, we find that the optimal policy is generally to apply treatments over budworms and to harvest the forest at a sustainable rate, which confirms that the current management programs used in Eastern Canada are welfare-improving relative to letting an outbreak run its course. The time path for our baseline scenario indicates that budworms can be treated down to endemic levels quickly. Sensitivity analysis describes scenarios where budworm levels will rebound every year as well as scenarios where the optimal policy is to clearcut the forest as quickly as possible. Chapter 3 considers the pre-outbreak monitoring phase for spruce budworm management. This context is informed by the Early Intervention Strategy, a management practice that is currently being successfully employed in New Brunswick and other Maritime provinces. EIS requires extensive monitoring and proactive treatment. As such, we adapt a model known as CESAT to determine the locations for which EIS would yield positive net benefits in eastern Quebec. Under our baseline scenario, we find that EIS is optimal in some zones bordering New Brunswick, which indicates that EIS is unlikely to be welfare-improving over current management practices used in Quebec. Under different assumptions, however, we find that EIS is optimal across a much larger landscape, yielding millions of CAD net benefits over a thirty year horizon.Item SUBSIDIES FOR DOMESTIC TECHNOLOGY ADOPTION UNDER HETEROGENEOUS TREATMENT EFFECTS(2024) Lopez Aguilar, Javier Alejandro; Battistin, Erich; Agricultural and Resource Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Governments and NGOs in developing countries offer subsidies to encourage the adoption of beneficial domestic technologies to generate positive externalities and improve access for poorer households. However, these subsidies may be mistargeted if the benefits come from the continued use of the technology, which is not guaranteed by its initial take-up. This dissertation examines the impact of a subsidy to promote the adoption of a rainwater harvesting (RWH) technology on the water restrictions residents of poor neighborhoods in Mexico City face. I explore this topic theoretically and empirically in three main chapters. In the first chapter, I outline a simple economic model of technology adoption and treatment effects. The model shows how exogenous changes to the subsidy can identify the treatment effects for different types of households, characterized by their willingness to pay (WTP) for the technology. To overcome the challenge of rare exogenous variation in subsidy rates and unobservable WTP, I propose the use of contingent valuation (CV) methods. These methods can exogenously generate variation in hypothetical subsidies and provide insights into the distribution of WTP in the relevant sample. The model is then completed by incorporating the CV information for empirical analysis. This approach may be valuable when randomized interventions are unfeasible due to institutional or budget constraints. In the second chapter, I empirically estimate the effects of the RWH Program in Mexico City on the time households spend obtaining water and the likelihood of postponing daily activities due to the lack of water. I employ the framework developed in the first chapter and local instrumental variable methods for the estimation. The data for this analysis was collected among all program participants in 2021 in partnership with the implementing agency. I find that the usage and causal effects of the RWH technology improve with the households' WTP. High-WTP households save 5 hours per week in water procurement time and reduce postponement of daily activities due to water scarcity by 25 percentage points. Conversely, low-WTP households are less likely to use the technology, yielding negligible benefits. The empirical analysis has significant policy implications. In the third chapter, I simulate counterfactual policies and show that adjusting the subsidy structure could enhance the average benefits of the RWH Program. Specifically, introducing enrollment fees that are a fraction of the total cost of the technology could consistently improve the average impact on recipients. These fees do not seem to disproportionately affect poorer households or those facing more stringent water restrictions, suggesting a potential avenue for policy refinement.Item ESSAYS IN CORPORATE SUSTAINABILITY(2024) Pi, Xueting; Epanchin-Niell, Rebecca; Smith, Cory; Agricultural and Resource Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This dissertation comprises three essays that examine various aspects of corporate environmental sustainability. Chapter 1 studies the impact of legal expertise in corporate leadership on improving corporate environmental sustainability performance by focusing on the role of general counsels (GC). Utilizing firm-level ESG data from 2002 to 2020 and employing probit model, while controlling for a host of firm characteristics, I find that firms with GCs in their top management teams are more likely to achieve better environmental performance, notably in emissions reduction. The relationship is robust to the models using peer firm GC ratio as an instrumental variable as well including industry fixed effects. However, these firms also tend to report higher greenhouse gas emissions, suggesting potential greenwashing. The improved environmental scores can be partially explained by GC firms establishing good awareness of climate change risk and opportunities as well as environmental training. In Chapter 2, an environmental regulation aiming energy consumption reduction is evaluated regarding the impacts on firm green innovation. In 2006, the Chinese central government introduced a policy mandating significant reductions in energy consumption by the top energy-consuming enterprises to achieve energy conservation objectives. This paper investigate the impact of this pivotal energy regulation aimed at the most energy-intensive Chinese manufacturers on their green innovation endeavors. Leveraging micro-level enterprise data and employing generalized difference-in-differences (DID) research designs, this study demonstrates that more stringent environmental regulation leads to a 2 to 4 percent increase in corporate green innovation. The findings remain robust across various alternative control groups and green innovation metrics. Chapter 3 investigates the interaction between wind energy development and biodiversity conservation. The rapid expansion of wind energy development represents significant progress towards achieving sustainable energy goals, but also can be accompanied by negative impacts on eagle fatal- ities and biodiversity. We investigate wind energy firms’ participation in golden eagle conservation, as represented by wind facilities’ choice to obtain an eagle incidental take permit. Under the US Eagle Protection Act, even unintentional take of golden eagles without an incidental take permit is illegal, and firms must mitigate or offset anticipated harm to obtain a permit. We combine theory and empirical analysis to explore the factors driving wind energy firms’ decisions on permitting. We find that golden eagle exposure and collision risk, as well as noncompliance detection likelihood and penalty intensity, positively influence firms’ permitting inclination. Current low rate of par- ticipation in permitting could be attributable to less intensive enforcement and the perception of low expected penalty costs for noncompliance compared to relatively high permitting costs.Item 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.Item 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.