VictorJuiz/thesis huggingface dataset:
Essays in political methodology
Keywords: Political Science.

This dissertation is comprised of four chapters, each of which is a freestanding essay on a topic in political methodology. Chapter 1 introduces a new approach to power analysis in the context of estimating a local average treatment effect (LATE), where the study subjects exhibit noncompliance with treatment assignment. Chapter 2 introduces a new method in causal mediation analysis, specifically to compare the mediation effects of different treatments via a common mediator. Chapter 3 focuses on analyzing treatment effect conditionality, in particular a variant called "causal moderation, " which implies that intervention upon a third (moderator) variable would alter the treatment effect. Chapter 4 proposes a set of dynamic assignment mechanisms.
Essays in public economics
Keywords: Economics.

This dissertation explores several topics in public economics related to income inequality, taxation, and redistribution. The first chapter argues that labor supply elasticities encode information about the determinants of income inequality, showing how reduced-form labor supply elasticities can be used to isolate the components of income due to productivities vs. preferences. The second chapter investigates a previously unexplored rationale for imposing conditions on cash transfers in developing countries, arguing that conditions based on children's school enrollment may actually improve the targeting of transfers to low consumption households. The third chapter explores how our theoretical understanding of optimal income taxation changes if we allow for the possibility that individuals jump discontinuously around the tax schedule in response to small changes in tax rates.
Essays in risk and public externalities
Keywords: Management Science and Engineering.

Over the past fifty years, financial and legal theory have predicted that owners of firms may have incentives to take risks that have positive expected value from the perspective of firms' equity holders but negative expected value from the perspective of total firm value and of society as a whole. These incentives stem from the fact that a firm's equity holders can enjoy potentially unlimited upside payoffs when risks turn out well, but have capped downside payoffs equal to the value of their equity holdings. Theory also predicts that the lower the value of those equity holdings (relative to total firm assets), the more pronounced these incentive effects may become. This dissertation encompasses three pieces of research that investigate these theoretical matters empirically. The investigations provide empirical evidence amongst banks and amongst industrial firms that as the value of equity (relative to assets) decreases, socially sub-optimal risk-taking increases. The investigations also provide empirical evidence that when a legal change increases the extent to which industrial firms' creditors will bear losses on account of harms that a bankruptcy debtor has caused to third parties, those creditors can exert their influence on borrowers to constrain their socially inefficient risk-taking.
Essays in trade, innovation, and productivity
Keywords: Economics.

This dissertation explores the determinants of firms' productivity growth and innovation activities. The first chapter studies the local technology spillover effects originated from multinational firms' innovation activities. The second chapter discusses the impact of import competition from China on U.S. firms' innovation activities. The third chapter introduces a new measure of firm-level regulation, and examines the consequences of rising regulation intensity in the U.S. on firms' production choices. Chapter 1 identifies the causal impact of U.S. multinationals' technology advances on their subsidiaries and the nearby domestic firms' productivity in China. By combining firm-level panel data from both the U.S. and China, I match U.S. multinationals with their manufacturing subsidiaries in China and measure the multinationals' technology stocks based on their patenting activities. To address potential endogeneity concerns, I introduce an instrumental variable strategy based on the U.S. state level R& D tax credit policies. I find multinationals' technology improvements induce increase in the output and total factor productivity (TFP) of both their subsidiaries and domestic firms in local areas. The magnitude of technology spillovers hinges on local firms' absorptive capacities, and their technological connections to the multinationals. Chapter 2 (co-authored with Rui Xu) analyzes the impact of rising import competition from China on U.S. innovative activities. Using Compustat data, we find that import competition induces R& D expenditures to be reallocated towards more productive and more profitable firms within each industry. Such reallocation effect has the potential to offset the average drop in firm-level R& D identified in the previous literature. Indeed, our quantitative analysis shows no adverse impact of import competition on aggregate R& D expenditures. Taking the analysis beyond manufacturing, we find that import competition has led to reallocation of researchers towards booming service industries, including business and repairs, personal, and financial services. Chapter 3 (co-authored with Constantine Yannelis) introduces a new measure of firm-level regulation. We find that more regulation increases labor and capital inputs. Productivity decreases, which is consistent with a model of regulation inducing non-productive investment. We employ two empirical strategies to identify the causal impact of regulation on firms, first, utilizing structural breaks and industry level regulation changes, and second, computing predicted industry level regulation measures as instruments. We conduct an event study using the surprise 2016 US election results. Firms with higher Dodd-Frank exposure exhibited higher returns following an increase in the probability of repeal.
Essays on industrial organization
Keywords: Economics.

This dissertation comprises three papers. The first, "Strategic Exploration: Search and Learning in the UK Oil Industry" investigates the effects of information spillovers in oil exploration. I use data covering the history of offshore oil and gas wells in the UK to measure the effect of information spillovers on industry profits and compute counterfactual property rights allocations that minimize the free riding problem. I find evidence of spatial learning across license blocks and information spillovers between firms exploring the same region -- firms are more likely to drill exploration wells after rival firms have made discoveries nearby. To evaluate the effect of these spillovers on industry profit, I estimate a structural model of the firm's dynamic exploration problem in which firms have spatially correlated beliefs about the location of oil deposits which they update after observing well outcomes. Since firms are forward looking they have an incentive to delay exploration if they are able to observe the results of competitors' wells. On the other hand, if firms are unable to learn from each other's exploration this can lead to inefficient duplicative exploration of unproductive regions. Policy simulations using the estimated model highlight the trade-off between discouraging free riding and encouraging efficient cumulative research - stronger property rights over exploration well data increase the rate of exploration, while weaker property rights increase the efficiency and speed of learning but reduce the rate of exploration. The findings relate to the general problem of the design of property rights in R& D, for example the optimal breadth of patents. The second paper, "You Can Lead a Horse to Water: Spatial Learning and Path Dependence in Consumer Search, " coauthored with Gregory Lewis, develops a model of the consumer's search and learning problem in online retail that is based on a similar "spatial learning" framework. We show that a model of search in which consumers make inferences from those products they observe to similar, unobserved products can explain patterns in data on online consumer behavior. We estimate the model using data on the sequence of products viewed by consumers shopping for digital cameras, and show in a counterfactual how search platforms can manipulate consumers beliefs to change their search paths. The third paper, "Trade-ins and Transaction Costs in the Market for Used Business Jets, " studies the interaction between the markets for new and used durable goods and the incentive for manufacturers to buy back and resell used units. I quantify the equilibrium effects of manufacturer buyback schemes in the market for used business jets. I find that removing buyback decreases demand for new jets among replacement buyers by 45% at fixed prices and raises used jet prices by 7% in equilibrium. Although the effect on used jet prices induces substitution towards new jets, manufacturer revenue is lower without buyback.
Essays on market design
Keywords: Economics.

This thesis consists of four essays on mechanism and market design. The first essay studies mechanism design in dynamic environments and establishes a sufficient condition for full surplus extraction and implementation. The second essay studies information acquisition in a matching problem and considers optimal information design. The third and fourth essays study the matching size in the assignment problems. The third essay characterizes the upperbound of the matching size achieved by the random serial dictatorship mechanism. The fourth essay shows that (i) the standard mechanism fails to achieve a large matching size when we have generalized constraints on the set of feasible matchings, and (ii) the alternative mechanism we propose always generate a large matching.
Essays on partisan polarization
Keywords: Political Science.

This dissertation studies the role of partisanship in American's non-political behaviors. I combine survey, web search, and behavioral data to examine the role of a change in the party of the presidency in partisans' health and purchasing behaviors. In two of the three cases studied, Americans whose party lost the presidency exhibited significant differences in their behaviors before and after the election.I used data from the George W Bush and Barack Obama administration to examine partisan shift in vaccination behavior, and found that presidential out-partisans became less likely to view vaccines as safe and less likely to vaccinate their children after their party lost an election. Furthermore, these differences were significantly mediated by partisans' level of government trust, suggesting that loss of trust in the federal government accounts for shift is partisan vaccination rates. Next, I used web search and DMV car registration data to examine partisan shifts in large purchases (cars, houses, and the stock market) after the 2016 election. I find that Democrats became less likely to search for cars and houses, and less likely to register new cars after their party lost the 2016 election. Finally, I examine web searches for mental health related terms among Democrats, Republicans, English-only searchers, and Spanish-speaking searchers in the wake of the 2016 election. While there were significant and sustained increases in searches for terms relating to mental distress among the Spanish-speaking searchers, there were no changes in searches among Democrats, even though their party had just lost the election. These findings suggest that while partisanship has significant and far-reaching implications on Americans' political behaviors, some reported partisan differences in behavior are the result of expressive reporting.
Essays on public funding for private innovation
Keywords: Management Science and Engineering.

Despite the significant annual expenditure of public (government) research and development (R& D) funding allocated to private, for-profit firms, research is unclear as to if whether or not public funding is positively associated with firm performance. To partially address this gap, in three essays I examine the most common funding tie between public organizations and private firms in the U.S. - public-private R& D relationships. In the first two essays, I conceptualize public-private R& D relationships as institutional hybrids and argue and show that relative to technologies developed without a public-sector partner, the institutional conflict underlying public-private R& D relationships is positively related to the creation of valuable and destabilizing technologies. To provide support for my institutional hybrids' hypotheses, I employ a novel machine learning-matching method to examine all patented technologies in the U.S. between the years 1982-2012. In the final essay, I focus on technology ventures (i.e., start-ups) that form a contractual R& D relationship with a public-consumer (e.g., NASA, DoD) and show that these start-ups produce technologies faster and survive longer than their non-contracted peers. However, due to the stabilizing dependencies inherent in public-consumer relationships, these ventures also experience slower growth. I conclude with management and policy implications.
Essays on the design and analysis of markets
Keywords: Business.

This dissertation is a collection of essays on the design and analysis of markets. I propose ways to change the rules of existing market mechanisms and analyze how these changes can increase market efficiency, and I develop empirical methods for analyzing market performance. Chapter 2 proposes a way to measure the manipulability of derivative contract markets. Chapter 3 proposes a new kind of license for allocating natural resource use rights. Chapter 4 develops general empirical methods based on mechanism design theory for analyzing a large class of trading games.
Essays on the economics of forced migration : evidence from Syrians in the Levant
Keywords: Economics.

This dissertation explores three leading, policy-relevant questions on migration related to conflict, focusing on Syrian refugees in Jordan, Lebanon, and Iraq. In the first chapter, I study the effects of living in a camp relative to self-settling in the same country. I find that camp residence reduces household income, but the gap is less than the rent saved; I argue that, in some settings, camps can be an efficient subsidy to refugees willing to opt out of urban areas. In the second chapter, I study the returns to leaving the Syrian Civil War. I find the differences between staying and leaving are minimal for most destinations across mortality, employment, education, and satisfaction. In the third chapter, joint with Ragui Assaad and Mohamed Saleh, I study the effects of Syrian refugees on the education of Jordanian children. I find that Syrians did not affect the attainment of Jordanians, thanks in large part to a second, donor-funded shift in the most affected areas.
Estimating Effective Electrochemical Parameters for Li-ion Battery Models with Convolutional Neural Networks and Minkowski Tensors
Keywords:  Department of Energy Resources Engineering
Li-ion Batteries
Convolutional Neural Networks
Multiscale Modeling
Electrochemistry
Department of Energy Resources Engineering
Stanford University
Thesis

Lithium-ion batteries (LIBs) have enabled a revolution in consumer electronics due to their exceptional energy and power density. Upscaling this technology from cell phone size (~10 Wh) to electric vehicle (~30-100 kWh) and grid storage size (>1 MWh) remains a challenge, however, partly due to the poor ability of understanding and predicting the microstructural behavior of such large systems. Since phenomena that occur at the microscale have a significant impact on system performance, it is crucial to accurately characterize these effects when modeling battery operation. This work thus focuses on incorporating microstructural electrode phenomena in macroscopic battery models to improve their capability to predict key battery performance metrics. This type of understanding improves the accuracy and computational efficiency of battery algorithms and can enable battery systems to be effectively designed to meet energy, calendar life, and safety requirements, and thus accelerate the adoption of electric vehicles and batteries as grid storage devices.
First, a multiscale framework for modeling the electrochemical behavior of LIBs is developed via homogenization. This framework establishes a closure problem, which is solved on a representative volume element (RVE) of the electrode microstructure, for determining effective properties such as diffusion and conductivity. The solution to this closure problem requires solving a coupled set of partial differential equations (PDEs), resulting in simplifying assumptions such as single spherical particles, which introduces inaccuracies because transport parameters are highly dependent on morphology. Thus, a Convolutional Neural Network (CNN) is developed for computational efficiency. The CNN, which is trained from solutions to the closure problem on computer-generated images representing various electrode morphologies, accurately predicts transport properties that can be used in macroscopic models. Results demonstrate that the CNN is significantly more accurate than the frequently-used Bruggeman relation and efficient enough for real-time quantification of evolving architectures. The CNN is further validated with sensitivity analysis and is applied to real SEM images and accurately predicts effective properties.
Next, the relationship between Minkowski tensors, which are powerful geometric descriptors for porous media calculated via integration, and electrochemical properties is studied. The Minkowski tensor values are then incorporated into the previous CNN by adding them in as nodes in a hidden layer to improve parameter estimation. This framework demonstrates how computer vision tools can be used to predict the solution of partial differential equations, which is a powerful model reduction technique that can be applied across many fields.
Étale Steenrod operations and the Artin-Tate pairing
Keywords: Mathematics.

We prove a 1966 conjecture of Tate concerning the Artin-Tate pairing on the Brauer group of a surface over a finite field, which is the analogue of the Cassels-Tate pairing. Tate asked if this pairing is always alternating and we find an affirmative answer, which is somewhat surprising in view of the work of Poonen-Stoll on the Cassels-Tate pairing. Our method is based on studying a connection between the Artin-Tate pairing and (generalizations of) Steenrod operations in etale cohomology. Inspired by an analogy to the algebraic topology of manifolds, we develop tools allowing us to calculate the relevant etale Steenrod operations in terms of characteristic classes.
Ethno-religious diversity and recovery after conflict in post-ISIL Iraq: a geospatial approach
Keywords: International Relations
Honors Thesis
ISIL
ISIS
post-conflict
reconstruction
diversity
ethnic
religious
ethno-religious
Thesis

After domestic conflict, why do some settlements recover faster than others? The problem of post-conflict reconstruction regularly attracts billions of aid dollars and carries hefty humanitarian and security implications, but little empirical work has focused on what causes differences in post-conflict recovery at the sub-state level. I explore the variation in recovery speed among Iraqi villages after the 2014-2017 Islamic State in Iraq and the Levant (ISIL) insurgency and focus primarily on the role of ethno-religious diversity in explaining the differences. Using satellite-observed nighttime light emissions as a proxy for economic activity, I construct an 81-month panel of economic output in 351 Iraqi settlements occupied by ISIL. This information is combined with settlement-level data on ethno-religious composition. In spatial autoregression and generalized synthetic control approaches, I evaluate the causal effect of ethno-religious diversity on post-conflict recovery across space and time. The results show that diversity has a large and significant negative influence on recovery. This result is robust to a variety of different specifications, and the magnitude of the effect grows over time. I argue that diversity slows reconstruction because it alters the local dynamics of security and cooperation and alters the strategies of local elites. Broadly, my findings support constructivist views on identity which suggest ethnic and religious identities can become “activated” in certain social conditions.
Euclidean-equivariant functions on three-dimensional point clouds
Keywords: Physics.

We present a type of neural network that is locally equivariant to 3D rotations, translations, and permutations of points at every layer. Local 3D rotation equivariance removes the need for data augmentation to identify features in arbitrary orientations. These networks use convolution filters built from spherical harmonics; due to the mathematical consequences of this filter choice, each layer accepts as input (and guarantees as output) scalars, vectors, and higher-order tensors, in the geometric sense of these terms. We exhibit applications of these networks to supervised learning tasks in structural biology.
Eutectic liquids for high-energy density flow batteries
Keywords: Materials Science and Engineering.

Harnessing variable wind and solar resources for most of our energy use will require advanced energy storage options. Flow batteries have an attractive battery architecture due to their scalability, long cycle-life, and power-to-energy tunability. However, the low energy density of flow batteries (~10-50 Wh/kg practical) limits their application. A significant hurdle to high-energy density flow batteries is finding negolytes and posolytes that remain in the liquid state at extremely high concentrations of redox-active species. One strategy to overcome this hurdle is to employ eutectic mixing properties for the depression of melting points. This dissertation focuses on the prospects of using Na-K liquid metal alloy, which has a eutectic melting point of -13 °C, as the negolyte in a flow battery at room temperature. At room temperature, liquid Na-K has an extremely high capacity of 580 mAh/g and a reduction potential of -2.9 V vs. SHE, assuming K+ is the mobile ion. First, we discuss the stability and compatibility of K-β''-alumina with Na-K. We find K- β''-alumina to be stable in phase and morphology to K-β''-alumina and to be an overwhelming conductor of K+ vs. Na+ when in contact with Na-K. These findings allowed us to demonstrate the cycling of batteries using Na-K, K-β''-alumina, and model aqueous and nonaqueous posolytes. Second, we discuss the different components of area-specific resistance in a Na-K-based flow battery. The interfaces on both sides of the K-β''-alumina can be large sources of impedance. On the Na-K [vertical line] K-β''-alumina interface, although Na-K does not wet K-β''-alumina at room temperature, we find some form of reactive wetting that decreases the interfacial resistance significantly. On the posolyte [vertical line] K-β''-alumina interface, we find that if the posolyte is aqueous, ion exchange of hydrogen/hydronium species and K+ increases the interfacial resistance substantially over time, but this can be greatly decreased through modifying the solution chemistry. These findings allowed us to achieve a high power density for a battery of this kind, 65 mW cm^-2 at 22 °C and > 100 mW cm^-2 at 57 °C. Third, we discuss our efforts to find an ideal posolyte by employing eutectic mixing to decrease the melting points of benzoquinone derivatives, which are redox-active organic molecules. We find that a regular solution model that assumes immiscible solids has predictive power for finding eutectic melting temperatures and compositions for mixtures of multiple components.