Economics Theses and Dissertations

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Essays on Competition in the Tech Industry and Platform Economies
(University of Oregon, 2024-08-07) Chang, Boyoon; Miller, Keaton
This dissertation examines competition dynamics within technology industries and platform-based economies. It examines three core aspects: acquisition strategies employed by incumbent firms, pricing strategies undertaken by an entrant firm, and the impact of antitrust regulatory interventions. Chapter 1 gives an overview of each dissertation chapter. In the second chapter, I investigate the acquisition strategies of major tech companies -- Google, Amazon, Apple, Meta, and Microsoft, and the interactive dynamics at play. This study separates the underlying motivations that drive these firms to make acquisition decisions, distinguishing between internal motives that seek scale economies and competitive motives that arise to prevent a competitive disadvantage. Using a rich dataset of acquisition records, I quantify the degree to which these firms are responsive to these distinct motivations. By accounting for forward-looking behavior of firms and relying on Markov Perfect Nash Equilibrium concept, I find a set of parameter estimates that make agents' observed actions yield higher expected future returns than their alternatives while also making their observed actions the best response to the moves of other market players. I find that competitive motives can explain a significant share of acquisition decisions, sometimes overshadowing the internal motives. The third chapter, co-authored with Keaton Miller, studies the commission rate policies of leading app distribution channels. It examines the effect of the regulatory intervention that aimed to change these policies. Specifically we investigate the effect of the legislation implemented in South Korea that allows developers to opt for mobile payment systems outside the conventionally required billing system of the app stores. We investigate how this regulation affected app performance, particularly among apps which were likely to be most influenced by this change. Using difference-in-differences and triple-difference-in-differences techniques, our finding suggests a potentially positive impact on app revenue, albeit with some degree of noise due to limited data. These results represent a novel finding, as they represent one of the first attempts to empirically measure the effects of this legislation. The fourth chapter explores whether aggressive pricing strategies can provide a competitive advantage to a smaller app distribution platform with a limited user base. Using proprietary data of one of the minor platforms in South Korea which charges significantly lower commission rate relative to the major players, I use difference-in-differences technique to examine key app performance metrics. I find that the volume of in-app traffic and the number of paid users increase, which implies that the strategy is successful in attracting user traffic on the platform in the short term, while I find these effects to be more significant in the short-run than in the longer-term. Overall, this dissertation provides comprehensive insights into competition within the tech industry and platform economies. It analyzes the regulatory effects aimed at spurring competition, examines the competition and strategies among incumbent firms, and explores the strategies employed by a new firm to compete against the established incumbents. This dissertation includes unpublished co-authored material.
Open Access
MARRIAGE MARKETS IN DEVELOPING COUNTRIES
(University of Oregon, 2024-08-07) Dudhe, Pramod; Chakraborty, Shankha
This dissertation studies, using the tools of dynamic macroeconomics, marriage markets in developing countries. The goal is to understand how the marriage market affects marital fertility, female labor supply and parents' human capital investment in girls. Chapter 1 provides the rationale for considering marriage markets in developing countries. It also presents an overview of the three research chapters. Chapter 2 develops an intergenerational model with gender bias in female education and dynamic marriage market. The model features skill-based positive assortative matching (PAM) and accounts for the gender-specific skill imbalance observed in developing countries. Within a household, spouses work in the labor market and decide about consumption, fertility and children’s education. We show how the equilibrium fertility distribution depends on different types of households that arise from marriage market matching and differences in fertility outcomes based on the quality-quantity tradeoff and parental skill levels. We estimate the model using Indian data, numerically derive the steady state and establish its local stability. Based on simulation results, the model does a good job of replicating the observed skill ratios. Chapter 3 builds on the model of chapter 2. The model is used to develop several policy-relevant results. An increase in marital sorting - as has been observed in India over time - worsens income inequality, and the gender bias in education and income. Elimination of gender bias as well as exogenous increases in returns to education and skilled-labor productivity contribute toward gender equality. Whereas gender-neutral subsidies are ineffective, the subsidies to poorer households aimed towards encouraging female higher education reduces the gender gap in education, labor supply and income. Dynamic policy analysis reveals that it takes 2 generations to reduce the gender gap in education by one-third. We conclude that gender-targeted policy can significantly weaken taste-based gender discrimination against female higher education. Chapter 4, joint work with Shankha Chakraborty, adapts the previous framework to better suit marriage markets in developing countries. A large percentage of marriages occur through family connections ("consensual arranged") that prioritize economic security and cultural values. Our framework captures the central tenet of these arranged marriages: parental decision to invest in girls' education is influenced by expectations of their marriage market outcome. We construct an intergenerational model with two-stage arranged-marriage market search model, which rationalizes parents' subjective gains from marrying off their offspring. The theoretical model is loosely calibrated to Indian data. Preliminary results indicate that there are significant returns to girls' education in the marriage market. In the future, we plan to extend the framework to identify the "social returns" of female education, considering its effect on marriage formation, marital fertility, labor supply and intergenerational education transmission. This dissertation includes previously unpublished coauthored material.
Open Access
EXPLORATIONS INTO THE FERTILITY TRANSITION AND FEMALE LABOR FORCE PARTICIPATION IN BANGLADESH
(University of Oregon, 2024-08-07) Siddiqui, SM Shihab; Burlando, Alfredo
This dissertation is comprised of three papers. Together, they investigate aspects of the fertility and female labor force transition in Bangladesh that started in the 1960s and continuing today. The dissertation is organized as follows: Chapter 1 summarizes the context, and provides an overview of the three research chapters. Chapter 2 analyzes the effect of increased industrial work opportunity on women's employment, reproductive behavior, and human capital accumulation. Using shift-share instrument, I find that increased industrial work opportunity increased women's employment significantly and reduced human capital accumulation very modestly among teenage girls. However, there was no effect on reproductive behavior. Chapter 3 provides the first comprehensive construction, to the best of my knowledge, of completed birth estimates of Bangladeshi women who were born all the way back in 1920. This exercise shows that the rural fertility transition begun with the 1945-50 cohort, within five years of the fertility transition in urban areas. I then present suggestive evidence that agrarian economic conditions, mediated by land availability, was a driver of the transition. Chapter 4 (co-authored with Shankha Chakraborty) utilizes Oaxaca-Blinder decompositions to examine why the female labor force participation rate has increased more in Bangladesh compared to contiguous Indian states since 1990s. We find that while women's education is positively associated with employment in Bangladesh, the reverse is true in the selected Indian states. We also find some evidence that women's relative education compared to men's has been an important factor in explaining this. Chapter 5 concludes the dissertation.
Open Access
ESSAYS IN ECONOMETRICS AND MACHINE LEARNING
(University of Oregon, 2024-08-07) O'Briant, Colleen; Miller, Keaton
This dissertation aims to enhance transparency in AI systems by integrating methods from Machine Learning and Econometrics, specifically focusing on Dynamic Discrete Choice (DDC) models. In Chapter 2, I compare the Nested Fixed Point (NFXP) algorithm from Econometrics with Max-Margin Inverse Reinforcement Learning (IRL) methods from AI/ML, using Monte-Carlo experiments to demonstrate that preference shocks from Econometrics can resolve fundamental identification issues in IRL. The simulation results show that while Projection IRL is slightly less accurate than NFXP, IRL significantly reduces computational demands, requiring 20 times fewer dynamic programming problems to be solved. Chapter 3 investigates the practical applications of these methods by analyzing publicly available 2013 taxi data to compare IRL and NFXP in estimating payoffs for New York City taxi drivers during the morning commute. The analysis highlights that IRL’s flatter objective function has the problem of allowing a broader range of acceptable payoff functions, however its feature expectation matching technique provides valuable feedback on the smoothing parameter for kernel density estimation of the transition probability function. This chapter offers recommendations and identifies potential drawbacks of using IRL, thereby deepening our understanding of the real-world performance of the algorithm.In Chapter 4, the dissertation explores how small business owners may misattribute noise for profit signals using an instrumental variables approach and a rich dataset of product ordering decisions by Washington State marijuana dispensaries over the first three years of recreational marijuana legalization. The study examines whether entrepreneurs’ predictions about product profitability are influenced by exogenous weather shocks, assessing if owners with previous retail experience make more informed decisions, if attentiveness improves over time, and if living further from the dispensary increases the likelihood of conflating weather shocks with profitability signals.
Open Access
Essays in Labor Economics
(University of Oregon, 2024-08-07) Wilson, Brock; Waddell, Glen
In Chapter 1, I exploit a policy change for U.S. federal workers’ pension benefits to estimate the effect of pension generosity on worker retirement, retention and recruitment. The policy increased pensions by 16%-25% or approximately $111,000. There is a 30% decrease in job quits for permanent workers. However, there is little evidence that pension generosity has an effect on new hires. This suggests salience may play a role in how workers value pensions. Additionally, I find a large heterogeneous labor supply response to pension generosity. Altogether, this shows that pension generosity is effective in retaining workers and may have important implications for workforce planning. In Chapter 2, I estimate a structural model of retirement that incorporates anticipatory labor responses. Under a naive model that assumes workers do not respond to financial incentives, fiscal costs will be underestimated. When workers dynamically respond to pension incentives, they delay their retirement to maximize their pension value which leads to higher fiscal costs. I estimate that, when not accounting for dynamic labor responses, fiscal costs will be underestimated by 8% to 20%. Altogether, policymakers intending to decrease public pension generosity may underestimate the fiscal costs without modeling anticipatory labor responses. Chapter 3 studies the effect of disability-based affirmative action on the federal workforce. We provide descriptive evidence there is an increase in representation of workers with disabilities. However, we find that this increase is relatively larger for less severe disabilities compared to more severe disabilities. Additionally, we find evidence there is a decrease in representation among agencies that satisfy the mandate. The results suggest that severity of disability may need to be considered when mandating disability-based affirmative action. This dissertation includes unpublished coauthored material.
Open Access
Essays in Behavioral Macroeconomics
(University of Oregon, 2024-08-07) Thompson, Jacob; McGough, Bruce
This dissertation investigates a class of DSGE models with bounded rationality where agents use recursively updated forecasts to form expectations of future vari- ables The two chapters explore the implications of the model builder’s choice of initial forecasting model with which to endow agents. Each chapter estimates a different New Keynesian DSGE model, varying this initial model and finds that this has sub- stantial impacts on parameter estimates as well as the ability of the model to fit macroeconomic data series. Chapter 1 estimates a small scale, purely forward-looking DSGE model but relaxes the assumption of rational expectations. In so doing, it outlines the computational challenges of estimating such a model and the solutions thereto. It also introduces the reader to a new class of Bayesian posterior sampler called Sequential Monte Carlo which has key advantages over Markov Chain Monte Carlo samplers for the estimation of models with Adaptive Learning. I find two notable results: first, I find that one can greatly improve the ability of the model to explain the data by training agents’ initial forecasting model on pre-sample data. Second, I find that, for this particular DSGE model, the estimated slope of the Phillips Curve is significantly greater than under Rational Expectations. Chapter 2 estimates a small-scale DSGE model with habit persistence in household consumption and inflation indexation by price-setting firm, thereby inducing mechan- ical persistence in both the output and inflation processes. This chapter shows that the improved data-fit from training sample based initial beliefs is robust to the in- clusion of mechanical lags. It also shows how initial forecasting models trained on pre-sample data cause the DSGE model to exhibit impulse response functions that show the “price puzzle” despite the additional restrictions of the DSGE model, and what restrictions to impose to avoid this outcome.
Open Access
Essays on Trust and Polarization in the Modern Era
(University of Oregon, 2024-08-07) Bivins, Tanner; Davis, Jonathan
This dissertation contains three empirical studies that examine how distinct interventions influence agent behavior and social outcomes in varying contexts. Leveraging both natural variation and lab experiments, each chapter contributes to the broader understanding of policy effectiveness, technological integration, and healthcare impacts within an economic framework. Chapter 1 examines the relationship between US primary election policies and electoral outcomes from 1976 to 2020. I use a difference-in-differences approach to investigate whether adopting less restrictive primary systems impacts legislator extremism and voter turnout. I find that expanding ballot access causes legislator ideology to shift toward the median voter. This moderating effect is even more pronounced for newly elected representatives and is driven mainly by non-partisan primary systems. Over the same period, I estimate a decrease in general election participation following the adoption of "open-type" primary systems. This paper offers a comprehensive view of primary election policies, underscoring the balance between enhancing representation and maintaining voter engagement. Chapter 2 is a collaborative project with Jiabin Wu, Ethan Holdahl, and Conner Weigand. In this study, we experimentally explore the impact of AI as a supportive tool for players in a two-player trust game. The game begins with the trustee sending a message to the trustor. In certain scenarios, the trustee is aided by the large language model (LLM) ChatGPT when composing this message. In other scenarios, the trustor uses GPT to interpret the message from the trustee, or both players may have access to GPT assistance. Our findings indicate that when the trustee utilizes GPT as a helper, it enhances cooperation with the trustor. Interestingly, this improvement in cooperation is not attributed to GPT's superior messaging skills. Instead, it appears that when the trustee has GPT's assistance, it encourages the trustor to scrutinize the trustee's message more closely, understanding that it could be genuinely crafted, a mixture of personal input and GPT suggestions, or solely generated by GPT. The detailed scrutiny by the trustor, and potentially the trustee's awareness of this scrutiny, aligns the beliefs of the trustor with those trustees who send either genuine or mixed messages, thereby fostering an environment that encourages the development of trust. Chapter 3 studies the relationship between stimulant medication and labor market outcomes in adults with Attention-deficit hyperactivity disorder (ADHD). In my analysis, I use linked employment and pharmaceutical data from the Medical Expenditure Panel Survey (MEPS) and leverage individual-level variation to estimate a two-way fixed effects regression. I find limited evidence to support a causal relationship between prescription behavior and employment, real wages, or weekly labor hours.
Open Access
Essays on Maritime Transport and International Trade
(University of Oregon, 2024-08-07) Economides, Philip; Wong, Woan Foong
This dissertation considers topics which dovetail studies of maritime trade and transportation. Using theoretical models, empirical identification and structural analysis, I provide novel evidence on three key facts; (i) the repositioning of empty container units is a key logistical practice in maritime shipping that enables the sustained service of global trade imbalances, (ii) advancements in container shipping technology through increased vessel capacity between 1977-2023 have introduced negative spillovers on cargo handling times at port, and (iii) the newly introduced estimated time of arrival (ETA) based port queuing system has contributed to decarbonization in the maritime shipping sector. In the first substantive chapter, I develop a model of containerized trade and transportation which embeds the logistical practice of container repositioning by transport operators. This involves bringing equipment to where it is most needed for further transport service, and may necessitate the transportation of empty containers when servicing commerce between countries with particularly large trade imbalances. I contrast the comparative statics of this model with novel container traffic data, collected individually from the key US ports. These reduced-form analyses demonstrate that the balanced exchange of container units can only be revealed upon accounting for empty units. Motivated by the recent passing of the Ocean Shipping Reform Act of 2022, I use a structural approach to examine the implications of restricting empty container outflows from the US in order to stimulate US exports. The results of this exercise suggest the policy backfires for the broader public. Although exports are stimulated by policymaker action, transport operators respond to this form of unconventional policy intervention by adjusting freight rates bilaterally. The resulting increase in freight rates for shipping routes destined for the US contributes to an overall reduction in trade activity and a pronounced decline in vessel capacity allocated towards the US containerized shipping market. In the second substantive chapter, Woan Foong Wong, Simon Fuchs and I explore how technological innovation and port conditions contribute to variation in individual containership dwell time events across the US. Our data documents vessel size, container capacity, and port concentration from January 1977 to December 2023. We observe a four-fold increase in US port visits, peaking in 2010, followed by a downward trend until 2023. This pattern coincides with an accelerated rate of entry among the largest categories of containership classes. We suggest that transport operators are increasingly relying on improved vessel technology to meet growing demand for trade, rather than by supplying more vessels. Despite volume growing over time, average dwell times across US ports have remained centered around 2.4 days. Our empirical results suggest that this status quo is maintained by offsetting mechanisms; (i) larger vessels representing greater unloading efficiencies, and (ii) increased port traffic volumes introduce stronger negative spillover effects on visiting vessels. In the third substantive chapter, I examine how logistical practices by port authorities can influence vessel emissions. I use the case study of San Pedro Bay, California, which introduced a new vessel queuing system. Under the former system, vessels would be required to enter within 25 nautical miles of the ports of Los Angeles and Long Beach before being eligible to be admitted to the vessel queue. Additionally, those awaiting service could anchor near the port area or drift nearby. After observing a swelling of anchorage zone and drift areas use, authorities introduced a queuing system in which each vessel's calculated time of arrival determined their queue position and mandated no idling within a 150 nautical mile area of the ports. I find evidence which suggests that the policy slowed down inbound vessels, reduced idling time prior to port admittance, but increased the extent to which vessels would reposition while waiting. Accounting for all three factors, I find that the policy contributed to a 30.2% decline in containership emissions relative to control ports along the US West Coast. The dissertation includes previously unpublished co-authored research.
Open Access
Sticky Information and Economic Dynamics
(University of Oregon, 2024-08-07) hart, evan; Piger, Jeremy
In this dissertation, I investigate economic dynamics under the sticky information model as- sumption. First, I propose a novel method for evaluating the likelihood of a nonlinear model with time-varying parameters and endogenous variables. Using this method, I estimate model param- eters and unobserved time-varying parameters of the sticky information Phillips curve. Finally, I adapt a bounded rationality assumption to an endogenous sticky information model, further enriching our understanding of economic behavior under these conditions.In Chapter 1, I propose a method to evaluate the likelihood of a nonlinear model with time- varying parameters and endogenous variables. Existing techniques to estimate time-varying param- eter models with endogenous variables are restricted to conditionally linear models. The proposed approach modifies a Sequential Monte Carlo filter to evaluate the likelihood of a nonlinear process with an endogenous variable. The modified filter augments the typical measurement and state equations with an equation incorporating instrumental variables. I evaluate the performance of a Bayesian estimator based on the likelihood calculation using simulations and find that the approach generates accurate estimates of both parameters and the unobserved time-varying parameter. In Chapter 2, I analyze the empirical evidence of variation in a structural parameter of the sticky information Phillips curve. This involves scrutinizing both the statistical significance of the variation and its economic implications. Upon examination, I discover a systematic trend in firms’ attention to relevant macroeconomic conditions, indicating a decline in attention over time. In Chapter 3, I study the stability of equilibrium in a general equilibrium model with information frictions. The equilibrium attentiveness rate is stable under a decreasing gain adaptive learning scheme. This stability motivates a review of the transition between equilibrium rates; a drop in the cost of gathering and processing information is used to shift the equilibrium. The attentiveness rate immediately jumps and increases asymptotically, approaching the new equilibrium.
Open Access
ESSAYS ON MONETARY TRANSMISSION AND BANKING
(University of Oregon, 2024-08-07) Nikolaishvili, Giorgi; Piger, Jeremy
The commercial banking sector in the United States comprises numerous small, local (community) banks primarily focused on lending to small borrowers in their respective local economies, alongside a smaller group of large, geographically-diversified (non-community) banks that cater to larger borrowers. On average, the lending practices and business models of these two types of banks different substantially. In this dissertation, I analyze the macroeconomic implications of the lending practices of community banks, along with the geographical factors driving their performance dynamics, using a novel method of impulse response function decomposition and existing high-dimensional time-series econometric methodologies, respectively. In brief, I find that the extent of national comovement in community bank performance has increased in recent decades, and that community bank lending plays a significant role in the transmission of monetary policy despite the decline in the presence of community banks relative to that of their noncommunity counterparts. The second chapter makes a methodological contribution, which informs the analysis of the role of community bank lending in monetary policy transmission in the third chapter. In this chapter, I formulate the concept of a pass-throughimpulse response function (PT-IRF), which captures the contribution of any given subsystem of a greater dynamical system to the net effect of the propagation of a structural shock. I also describe methods of empirically estimating and performing inference on PT-IRFs using vector autoregressions and local projections. Finally, I demonstrate the applicability of PT-IRFs by estimating and empirically testing the effect of a monetary policy shock on unemployment through changes in bank lending in a small autoregressive model. The third chapter examines how heterogeneity in lending practices acrosscommunity and noncommunity banks influences the transmission of monetary policy to the real economy. Using PT-IRFs, I quantify the contributions of community versus noncommunity bank lending to the dynamic effect of a monetary policy shock on output. My findings show that noncommunity bank lending amplifies the contractionary effects of a monetary tightening in the short run, whereas community bank lending has a stronger amplificatory contribution in the medium run. These results suggest that a continued decline in the relative presence of community banks may lead to a subsequent decline in the persistence of monetary transmission. Furthermore, the adverse impact of a monetary tightening on spending must concentrate more persistently among small businesses and agricultural producers in remote rural areas, since these borrower segments tend to heavily rely on community bank lending as a source of funds. The fourth chapter studies the comovement in community bank profitability dynamics at three different geographical levels. I use a hierarchical dynamic factor model to extract posterior distributions of national, regional, and state-level latent drivers of quarterly fluctuations in state-average community bank return-on-equity series for all 50 US states. The results show a decrease in the intensity of idiosyncratic performance dynamics since the global financial crisis, along with a near-uniform increase in national comovement. This finding implies an increase in the exposure of the community banking sector to systemic risk, suggesting a potential increase in fragility during future financial crises.
Open Access
Essays on Discrimination and Information Technology
(University of Oregon, 2024-08-07) Ren, Tamara; Davis, Jonathan
This dissertation investigates how decision-makers, such as teachers or law enforcement agencies, may discriminate against individuals from different racial and gender demographic groups in the context of technology usage. It analyzes the impact of seeing identifying information (such as names, photos, and emails) and signals of quality (such as sharing information about one's past in an email) on decisions. This dissertation also explores how leveraging technology may reduce the potential for discrimination by using the features on digital platforms to conceal identifying information from decision-makers or to incentivize objectivity and fairness in assessments. This dissertation includes unpublished coauthored material.
Open Access
The Complexities of Public Goods for a Diverse Public: Evidence from Gun Laws, Climate Policy, and Police Transparency
(University of Oregon, 2024-01-10) Stanford, Garrett; Rubin, Edward
This research examines three pressing social issues: tensions between lawenforcement and the public, climate change policy options, and firearms control laws. Chapter 2 and Chapter 3 use field and survey-based experiments to collect primary data. They estimate novel measures, respectively, of police behavior and public preferences concerning climate change policy. Chapter 4 uses newly available administrative data to understand the consequences of a recently passed firearms control law. In Chapter 2, I test for evidence of racial and gender biases in one aspect of policeinteractions with the public in the United States. Using a so-called “correspondence” study, I test whether police departments respond differently to requests for information about how to lodge a formal complaint against an officer in the department depending on the perceived race/ethnicity and gender of the complainant. The study’s experimental design allows me to examine police behavior quantitatively without relying on police- provided administrative data. Results for a nationwide random sample of police departments suggest that police departments are less likely to respond to Black and Hispanic individuals than White individuals. Examining the interaction of race/ethnicity and gender, I find police departments are most likely to respond to White males and least likely to respond to Black and Hispanic males. Chapter 3 reports upon the results from a set of survey-based choice experimentsdesigned to assess state-level demand for carbon cap-and-trade programs with different attributes. The evidence confirms that these state-level preferences are strongly heterogeneous with respect to political ideologies and opinions about climate change. Our models allow us to calculate the implied social benefits of carbon emissions reductions. We estimate the marginal rate of substitution between “carbon” jobs and “green” jobs for different preference classes. We then use our estimates to model how support for different types of cap-and-trade programs varies across the United States. Methodologically, we account for systematic sample selection of respondents in our estimating sample relative to the quota-based sample of invitees from our commercial internet panel. In Chapter 4, we examine the (un)intended effects of Oregon’s new firearmscontrol law: Measure 114. Narrowly passing by a popular referendum vote in November 2022, Measure 114 aimed to increase firearms licensing requirements and restrict access to high-capacity magazines for ammunitions. We use data from the FBI’s National Instant Criminal Background Check System and an administrative dataset provided by the Oregon State Police to measure the causal effect of the law on firearm sales. Results indicate that Measure 114 unintentionally motivated Oregonians to purchase an unprecedented increase in the number of firearms. This dissertation includes previously unpublished co-authored material.
Open Access
Three Essays in Applied Microeconomics
(University of Oregon, 2024-01-09) McDonough, Robert; Waddell, Glen
This dissertation examines three topics in applied microeconomics: econometric challenges created by student grade-point averaging, the causal effect of violent video games on crime, and spatial distortions created by the US social safety net. Chapter 1 (with Glen Waddell) considers the underlying combinatorics of grade-point averaging, and the evolution of a GPA as students take classes. We illustrate the implications for inference that relies on the comparison of students with similar GPAs. In the context of a regression discontinuity, researchers are most exposed to this sensitivity with fewer classes contributing to GPA and at smaller bandwidths. While larger bandwidths shield such estimators from this challenge, this accommodation relies on the assumption of sufficient overlap of student types—to the extent there is not, identification is again threatened. Chapter 2 (with Gretchen Gamrat) examines the causal relationship between violent video game releases and violent crime patterns. Using county-level variation in retail sales of “mature” video games, we leverage exogenous variation in exposure to identify corresponding changes in crime outcomes. Especially after high-profile violent crimes, policymakers and the news media frequently argue that increased exposure to violent games leads to increased violent crime. We find no such evidence. If anything, our analysis suggests that short-run decreases in violent crime, specifically violent sexual offenses, follow the release of mature video games. Chapter 3 (with Mark Colas) studies the effect of the US social safety net on household location choice. US social transfer programs vary substantially across states, incentivizing households to locate in states with more generous transfer programs. Further, transfer formulas often decrease in income, thereby rewarding low-income households for living in low-paying cities. We quantify these distortions by combining a spatial equilibrium model with a detailed model of transfer programs in the US. Chapter 4 concludes this dissertation. This dissertation includes previously both previously published and unpublished and co-authored material.
Open Access
Economics of Environmental and Public Health Policies
(University of Oregon, 2024-01-09) Zhang, Shan; Zou, Eric
This dissertation is comprised of three papers that investigate the effects of recycling policy, pollution, and public health policy. The first paper examines the impact of China's waste import ban on U.S. polltion emissions at the national and state level. The second paper studies the distributional effect of China's waste import policy on waste transfers across local communities in California. The third paper investigates people's willingness to pay for public health policies to protect the health of a community during the COVID-19 pandemic. Chapter 1 provides a comprehensive overview of each dissertation chapter. Chapter 2 analyzes the effect of China's Green Sword policy (waste import ban) on U.S. emissions at the national and state level. Using the synthetic control method, the study finds that many states experienced significant increases in methane emissions after the policy took effect, with the total U.S. methane emissions from the waste industry increasing by 10\%. The study also finds a positive correlation between the waste trade each state had with China before the ban and the increase in emissions after the policy, suggesting that the states that relied more on trading recyclable wastes with China were more affected by the policy. Chapter 3 examines the effects of the Green Sword policy on the relocation of solid waste pollution across local communities in California. Using detailed waste transfer data from California, the study finds that Black communities received more waste transfers before the policy, but after the policy, relatively more waste pollution relocated to lower-income White communities. The study identifies land costs as the primary explanation for this distributional effect. Chapter 4 (co-authored with Trudy Ann Cameron) utilizes a choice-experiment survey of U.S. residents to determine people's willingness to pay for public policies to reduce illnesses and premature deaths in their communities. The study estimates people's ex-ante willingness to pay to avoid the actual monthly totals of COVID-19 cases and deaths from March 2020 to April 2021 by county and month. The estimated aggregate willingness to pay across the U.S. adult population during this period is about 3 trillion dollars.
Open Access
Theoretical and Experimental Investigations into the Evolution of Populations and their Behavior
(University of Oregon, 2024-01-09) Holdahl, Ethan; Wu, Jiabin
This dissertation examines game theory and evolutionary dynamics, exploring strategic decision-making, social norm emergence, and inter-group conflicts. Chapter 2 focuses on stepping stones, recurrent classes that facilitate equilibrium transitions. An experiment tests their effectiveness in promoting the transition to a Pareto efficient equilibrium. Results show groups with stepping stones consistently achieve the high-payoff equilibrium, contrasting occasional failures in groups without them. Information about other players' payoffs is crucial, with complete information outperforming incomplete information. However, the effect diminishes with stepping stones, emphasizing their low-cost transitions. Players' decision-making behavior and factors influencing deviations are also examined. Chapter 3 explores the role of incomplete sampling in determining convergence to conventions in adaptive play. The chapter demonstrates that even minimal incomplete sampling is sufficient for convergence to occur in the 2x2 coordination game. The analysis also reveals that incomplete sampling criteria are often unnecessary, expanding the boundaries of adaptive play theory. The implications of incomplete sampling on the perturbed adaptive process are examined, identifying a robust resistance function that persists under different degrees of sampling. In Chapter 4, the effects of signaling in inter-group conflicts are investigated. The competitive advantage of costly signaling within groups is examined, and a model is developed to explore the dynamics of inter-group conflicts. The findings suggest that shorter periods of isolation and more efficient weapons favor the rise of signaling norms in societies. Overall, this dissertation provides valuable insights into game theory, evolutionary dynamics, and their implications for strategic decision-making, social norms, and inter-group conflicts. The findings contribute to interdisciplinary fields such as economics, sociology, and political science, offering a foundation for further research in these areas. This dissertation includes both previously published co-authored material and unpublished co-authored material.
Open Access
The Multifaceted Nature of Identity: Social Networks, Cognitive Constraints, and Economic Development
(University of Oregon, 2024-01-09) Huang, Hanyuan; Wu, Jiabin
This dissertation provides a deep exploration of identity. Three chapters present studies of the interplay between identity and various social, cultural, and economic factors from different angles. The first chapter develops a theoretical framework for expressing cultural identity within social networks, taking into account individuals’ desire to conform and be unique. This leads to diverse expressions of cultural identity influenced by social structures. The second chapter proposes a model to explain the emergence of dominance hierarchies, where agents with limited cognitive abilities optimize their strategies in a social interaction game. This results in different types of hierarchical structures, providing insight into societal order. The final investigation focuses on ethnicity choice in mixed-ethnic families in modern China, highlighting the impact of economic development and education quality. It presents an intra-household bargaining model that explains changes in benefits, costs, and bargaining powers within families. The dissertation as a whole characterizes the multifaceted nature of identity, revealing its profound connections with social networks, cognitive processes, and economic development.This dissertation includes both previously published and co-authored material.
Open Access
The Trade Impact of Diplomatic Relations in Developing Countries: The Choice between China or Taiwan
(University of Oregon, 2024-01-09) Kamanga, Promise; Cristea, Anca
China is using the policy of diplomacy to increase its global influence, especially among developing countries. From 1995 to 2019, twenty-two developing countries from various parts of the world switched diplomatic allegiances from Taiwan to China. This dissertation evaluates how this diplomatic policy change affected various trade outcomes of the countries that switched allegiances. In summary, it finds that trade with Taiwan decreased, especially imports from there. For trade with China, the value of imports increased but that of exports decreased. This decrease in the value of exports spared the sectors for which the switching countries enjoyed comparative advantages.
Open Access
Essays in Applied Machine Learning and Causal Inference
(University of Oregon, 2022-10-26) Lennon, Connor; Waddell, Glen
This dissertation represents a study of how machine learning can be incorporated into existing econometric causal techniques, with explorationsboth in the costs and benefits of making that choice. The first chapter explores a simulated instrumental variables setting to evaluate the ease of incorporating unmodified machine learning techniques into the ”first stage“ problem. The first stage of two-stage least squares (2SLS) is a prediction problem—suggesting gains from utilizing ML in 2SLS’s first stage. However, little guidance exists on when ML helps 2SLS—or when it hurts. We investigate the implications of inserting ML into 2SLS, decomposing the bias into three informative components. Mechanically, ML-in-2SLS procedures face issues common to prediction and causal-inference settings—and their interaction. Through simulation, we show linear ML methods (e.g.post-Lasso) work “well,” while nonlinear methods (e.g.random forests, neural nets) generate substantial bias in second-stage estimates—some exceeding the bias of endogenous OLS. This work was performed in conjunction with professors Edward Rubin and Glen Waddell. The chapter author wrote simulation code, excepting the substantial portions used for table creation and to iterate over differing methods, to evaluate and run the methods tested in this chapter, and we designed the DGP function based on those found in Belloni, Chen, Chernozhukov, and Hansen (2012). The second chapter is an applied use of Machine Learning to evaluate an existing causal estimate of property value on suppression costs in the Wildfire Economics space. Models in use currently rely on excluding class A-D wildfires that burn fewer than 300 acres, use property values as an input and feature differential estimates for per-acre suppression costs in the Eastern and Western United States. However, restricting suppression cost estimates to large fires ignores wildfires that have high per-acre costs due to aggressive initial-attack strategies, and fires occurring in well-managed forests with fewer suppression requirements, which may lead SCI-derived estimates of cost to be biased and potentially be overly responsive to changes in local wealth. Using double/debiased vision transformers, SCI parameters overestimate the impact of property value as a contributor to suppression costs. This dissertation includes unpublished and co-authored material.
Open Access
Essays on India's Economic Development
(University of Oregon, 2022-10-04) Gupta, Saurabh; Chakraborty, Shankha
This dissertation is on the economic development of India during the past three decades with a focus on its changing industrial and household structure. Chapter 1 provides a brief introduction of the Indian economy and motivates the theme of the dissertation. In Chapter 2, I study the effects of transportation infrastructure on regional manufacturing activity. I exploit geographical and temporal variation in project implementation to argue for causal effects on the regional industrial outcomes. I investigate how highways can improve market competition between firms situated in geographically distant locations, and as a result, create incentives to invest in activities that improve productivity. The results show that highways had no direct effect on India’s manufacturing output growth and led to a decline in average manufacturing productivity. I argue that these results can be attributed to lack of improvements in allocative efficiency within regions, and slow movement of skilled labor into the manufacturing sector. These results are contrary to some recent work on India but in line with evidence presented in the wider literature on low-income countries In Chapter 3, I investigate the relationship between highways and female labor force participation (FLFP). Using census level data from India, I estimate how the construction of highways may have opened up market opportunities for households and consequently affected FLFP. I find that the effects are heterogeneous across districts with some districts experiencing an increase while others experiencing a decline in FLFP. The decline was driven mostly by married and educated women withdrawing from the manufacturing and services sectors. I also find suggestive evidence that highways led to an increase in labor force participation of low skilled women. In Chapter 4, jointly with Dr. Shankha Chakraborty, we examine how household decision making can explain India’s declining FLFP over the last three decades. We propose a tractable analytical model in which married women respond to opportunity costs of their labor hours when dividing their time between household and market production. The model incorporates cultural costs attached to female work and its negative effect on female labor supply. We highlight competing mechanisms at play that suggest a U-shaped pattern of FLFP in response to economic growth. Finally, Chapter 5 summarizes the results of the dissertation and presents a concluding remarks.
Open Access
Essays on Urban Housing and Gentrification
(University of Oregon, 2022-10-04) Briar, Cory; Colas, Mark
Cities are the locus of the overwhelming majority of economic activity in modern societies; understanding the interactions of urban trends and policies is crucial to achieving desired economic outcomes. This dissertations provides three papers characterizing the mechanisms of change in US cities over the last 30 years. After an introduction in chapter one, chapter two investigates the role of firm- sorting in the process of gentrification in Seattle, Washington between the yearsof 1990 and 2018, and finds that holding firm distributions fixed at 1990 levels leads to a significant attenuation of the process. Chapter three repeats the analysis of chapter two for the city of Portland, Oregon and compares results with those in Seattle. Chapter three investigates the connection between turnover in the housing market and modern rent control policy in San Francisco, California, and demonstrates the factors at play that lead to the deletion of older structures under said policy from the market.