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Three Essays in International Trade
No full textThesis (Ph.D.)--Michigan State University. Economics - Doctor of Philosophy, 2025Chapter 1: Anticipating Tariff Changes: Did American Importers Respond to Trump's 2016 Victory?As the biggest U.S. presidential election upset in recent decades, Donald Trump\u2019s 2016 victory introduced new uncertainties in the trade environment, including the potential for additional prohibitive tariffs. While it is well documented in the trade literature that firms anticipate and respond to scheduled tariff changes, it remains unclear whether this still holds when changes are uncertain and may happen at any moment, for example, following a contentious election. Focusing on the period between the 2016 election and the first round of China-specific tariffs in mid-2018, I empirically study if and how American importers reacted to potential tax hikes using U.S. Customs bills of lading data. By exploiting cross-product, origin, and time variations in tariff risks through a triple-difference approach, I find that importers facing higher risks stockpiled in response to Trump\u2019s election\u2014increasing their quarterly imports by around 5% through larger order sizes rather than increased order frequency. However, there is no evidence that firms expanded their trade network, diversified their sourcing portfolio, or diverted away from China during this period. The stockpiling behavior was more pronounced among smaller importers, which can partially be explained by the downstream nature of their purchases rather than differences in post-election entry/exit rates or input storability.Chapter 2: Local Political Environment and Importers' Stockpiling Behavior after the 2016 United States Presidential ElectionThis paper studies whether the local political environment surrounding a firm influenced its behavior in response to the 2016 U.S. presidential election and the subsequent threat of protectionist tariffs against China. Building on my prior work that documents stockpiling by American importers after Donald Trump's victory in anticipation of tariffs on Chinese goods, I examine whether firms located in more pro-Trump or anti-trade areas responded differently to the same risk. Using high-frequency bills of lading data linked to county- and state-level political measures, I employ a quadruple-difference framework to estimate the heterogeneity, or lack thereof, in stockpiling behavior across areas with different politics. The results suggest that, in general, local political alignment had no significant impact on firms\u2019 inventory strategies. While there is some suggestive evidence that small firms in red states stockpiled more, this effect disappears under the more granular county-level analysis. These results suggest that firm inventory decisions appear to be driven mainly by economic incentives, rather than by the political preferences of the surrounding community.Chapter 3: Transshipment Hubs, Trade, and Supply ChainsThe majority of global trade moves by sea through hub-and-spoke shipping networks. We investigate the returns to being a hub country by analyzing how global transshipment activity shapes its trade flows and supply chains over a decade. We find that most U.S. imports\u2014especially from smaller countries\u2014are transshipped via a few key hubs, and transshipment activity is positively correlated with trade. Leveraging the indirect nature of trade networks as an instrument, we find that transshipment increases both hub imports from origin countries and exports of downstream goods, highlighting its central role in shaping modern global trade and supply chain dynamics.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
Impulsive Control for Orbital Stabilization and Nonprehensile Manipulation
No full textThesis (Ph.D.)--Michigan State University. Mechanical Engineering - Doctor of Philosophy, 2025Several dynamical systems are underactuated, i.e., have fewer control inputs than the minimum number of generalized coordinates needed to describe the system. Underactuated dynamics arise commonly in legged robots, and in the study of robotic nonprehensile manipulation, which is manipulation of objects without grasping. The dynamics of such systems may additionally be hybrid and nonlinear. Many applications of underactuated systems require stable, repetitive motion; the problem of realizing such motion is challenging owing to the limited control inputs available. Impulsive control is shown to be an effective, and sometimes necessary, tool in stabilizing and transitioning between periodic orbits for underactuated systems.Gait design and stabilization for bipeds is an important control problem in underactuated systems. The problem of designing and stabilizing impact-free gaits for planar bipeds is addressed by defining a set of geometric constraints that eliminate foot-ground impact forces at the time of leg interchange. It is shown that a family of stable gaits, whose stride length and walking speed can be independently chosen, is guaranteed to exist. The efficacy of continuous and impulsive control, working in tandem, in stabilizing a desired gait and transitioning between distinct gaits is demonstrated.Nonprehensile manipulation of the devil-stick is investigated extensively. The devil-stick represents an extended object, described by orientation in addition to position, and controlling its motion without grasping is a challenging problem. Various underactuated devil-stick manipulation tasks are considered, including propeller motion using continuous forcing, and juggling using impulsive inputs. Devil-stick juggling in three dimensions is addressed by transforming the control problem to one of fixed point stabilization in a rotating reference frame. By varying the fixed point gradually with time, it is shown that a variety of maneuvers can be achieved. To address more complex underactuated juggling tasks, the concept of discrete virtual holonomic constraints is introduced. At the discrete instants when impulsive inputs are applied, the location of the center-of-mass of the devil-stick is specified in terms of its orientation angle. This yields the discrete zero dynamics, which provides conditions for stable juggling. An impulsive control design that enforces the discrete virtual holonomic constraint, and stabilizes a desired juggling motion is presented. The approach is studied in the context of propeller motion and planar juggling of the devil-stick.For experimental implementation of devil-stick juggling, the mechanics of impact on circular beams is investigated using a finite element approach that captures energy transfer to vibration modes. Simulations and experiments show spatial variation of the coefficient of restitution for impacts along the length of a pinned beam. A pinned beam is juggled using a general-purpose robot by synchronizing the motion of the robot directly to that of the beam using virtual holonomic constraints. The impact location on the beam and the velocity of the robot end-effector at impact are chosen based on the coefficient of restitution. Juggling in the presence of losses, delays, uncertainties, and hardware constraints is demonstrated.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
The Role of Dispositional Adherence in Viewer Engagement and Retrospective Imaginative Involvement
No full textThesis (Ph.D.)--Michigan State University. Communication - Doctor of Philosophy, 2025Stories often linger with us long after they end, shaping how we think and feel beyond the moment of viewing. This dissertation integrates Affective Disposition Theory (ADT) and Retrospective Imaginative Involvement (RII) to examine how moral evaluations of characters, specifically, dispositional adherence, or the degree to which good characters are rewarded and bad characters are punished, affect how viewers continue to engage with narratives after consumption. A controlled experiment (N = 155) exposed participants to one of two endings of Ladder 49, varying in dispositional adherence. Results showed that while dispositional adherence affected resolution satisfaction, it did not significantly alter post-viewing engagement. Instead, moral judgments of the protagonist, formed early in the narrative, were the strongest and most stable predictors of audience responses. Parasocial relationships and boundary expansion consistently predicted sustained imaginative involvement, whereas identification had a more selective role. These findings suggest that who the character might matter more than what happens to them. Long-term engagement arises less from moral resolution and more from enduring emotional connection and reflective immersion with morally grounded characters.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
LEAF DEMOGRAPHY, SPECTRAL VARIABILITY, AND HYDROLOGICAL- TOPOGRAPHIC CONTROLS ON AMAZON FOREST PRODUCTIVITY ACROSS SEASONS AND UNDER CLIMATE STRESS
No full textThesis (Ph.D.)--Michigan State University. Forestry - Doctor of Philosophy, 2025While the Amazon forest faces increasingly stronger and more frequent stressors, its resilience and stability under intensifying extreme climatic events remain uncertain and interpretation of signals detected by remote sensing platforms are still debated. The main controversy centers around the \u201cAmazon green-up\u201d since orbital satellite data suggest enhanced photosynthetic activity during the driest months and during droughts, presumably due to sun-sensor geometry artifacts. Even though new algorithms and several sources of evidence have been developed and presented, doubts still remain regarding the magnitude and authenticity of these signals. Terrain variability is typically overlooked in remote observations of the Amazon because measurements are typically aggregated into coarse orbital pixels, casting doubt on the generalizability of the observed seasonal and interannual patterns. Among these overlooked terrain characteristics, shallow water table areas (<5 m), covering ~50% of the Amazon basin, are argued to act as a drought refugia given the easier access to soil water by plants. These uncertainties highlight a major knowledge gap in linking remote sensing to underlying ecological processes. An intriguing framework can be derived from the leaf-demography-ontogeny hypothesis, which links Amazonian seasonal productivity to leaf demographic changes. This framework suggests satellites can retrieve leaf demographics to estimate forest productivity. Such an approach would further allow for testing of the hypothesis\u2019 generalizability across the Amazon basin. While recent studies provide indirect evidence linking leaf demographics to satellite vegetation indices, robust mechanistic confirmation and empirical evidence remain limited. Near-surface platforms, such as Unmanned Aerial Vehicles (UAVs), provide a critical link between field observations and satellites, though calibration and data integrity remain obstacles. Given all these challenges, the first chapter of this dissertation provides a brief overview of the dissertation. The second chapter focuses on testing the consistency of vegetation seasonality across multiple remote-sensing platforms, from coarse-resolution MODIS to finer-resolution Landsat 8 and Phenocam observations. Our results demonstrate that the widely debated Amazon green-up signal is genuine, robust across platforms, and likely caused by leaf demographic processes rather than sensor artifacts. The third chapter builds on this by presenting the first direct UAV-based multispectral evidence of Amazonian seasonal green-up, showing that canopy-level leaf demographic variation indeed drives seasonal spectral variation in high spatial resolution. The fourth chapter develops and validates a new spaceborne framework to test the leaf ontogeny hypothesis of photosynthesis at broad scale, demonstrating that spectral vegetation indices can infer leaf age cohorts and predict photosynthetic capacity across the Amazon basin. The fifth chapter introduces terrain complexity as a critical but overlooked factor in Amazon monitoring, with an emphasis on the role of variation in the depth to the soil water table. Using UAV data collected during the 2023-2034 Amazon drought, I show that spectral, thermal, and demographic signals differ significantly between forests growing on shallow versus deep water tables, revealing terrain-driven differences in resilience in the face of drought. The sixth chapter further explores terrain influences on forest structure by applying deep-learning approaches to LiDAR 2D point-cloud data, uncovering forest structural variation across hydrological gradients that traditional LiDAR metrics fail to capture. Together, these results demonstrate the importance of integrating multi-scale remote sensing approaches, ranging from orbital satellite to UAV to near-surface observations, with theoretical ecological approaches to advance the mechanistic understanding of Amazon forest productivity, and improve monitoring of tropical forest responses to a changing climateDescription based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
Towards improved high-resolution process-based model prediction of surface water availability in a changing climate
No full textThesis (Ph.D.)--Michigan State University. Civil Engineering - Doctor of Philosophy, 2025Climate change is threatening the reliability of water supplies for people and ecosystems in snowfed regions that are already water-stressed, such as the southwestern United States (U.S.). Thus, there is an urgent need for locally relevant predictions of future surface water availability to advance our understanding of the interplay between climate, hydrology, and water management, and inform adaptation. But the value of process-based land or hydrology model predictions of surface water availability is often compromised by their coarse resolution, deficiencies in the parametrization of hydrologic processes that result in substantial biases in runoff (and hence streamflow) and in its sensitivity to climate, and a lack of faithful representation of direct human impacts on surface water availability through reservoir regulation. This thesis improves land model parametrization of hydrologic processes and reservoir regulation to advance understanding of the interplay between climate, hydrology, and water management in water-stressed regions such as the southwestern U.S. Using a state-of-the-science land model, the controls on runoff sensitivity to changes in precipitation and temperature are first investigated in the snow-dominated headwaters of the Colorado River basin. Sophisticated variance-based sensitivity analysis reveals complex process-parameter interactions among subsurface, snow, and plant processes underlying model runoff climate sensitivities.Machine-learning-based model emulators are then used to constrain these processes with measurements, which circumvents the previously insurmountable hurdle of the immense computational cost of calibrating process-based models. Tested across the southwestern U.S. at 4 km spatial resolution, this approach improves natural streamflow prediction in all basins. Model coupled with two reservoir parametrizations shows that a data-driven reservoir parametrization informed by reservoir records of operation improves the prediction of water storage and outflow in major reservoirs compared to a generic parametrization \u2014 conditional on accurate model prediction of reservoir inflow. Model-based reconstructions of the past four decades indicate widespread increases in evapotranspiration and snowpack loss, which suppresses runoff. Water storage in major reservoirs has offset up to 40% of this deficit in surface water availability. Finally, this work presents projections of natural and regulated streamflow in the southwestern U.S. using a high-resolution (4 km) multi-model ensemble of three process-based Land and Hydrology Models (LHMs) and the two reservoir parametrizations driven by bias-adjusted and downscaled forcings from six Global Climate Models (GCMs) that follow four socioeconomic scenarios. Ensemble near-term projections (the next 25 years) reveal a wide range of outcomes of both increases and decreases in streamflow due to differences among GCMs and LHMs. But under high-risk (e.g., dry-warm) climate conditions, the ensemble shows a robust and widespread decrease in streamflow and reservoir storage across the southwestern U.S, suggesting a degradation in reservoir operational flexibility. The results and methods presented in this work should be useful for reducing uncertainty in future projections of regional surface water availability and improving the accuracy and robustness of process-based models to support research and practical applications.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
INTRA-MOLECULAR PROTEIN DYNAMICS IN LIQUID-LIQUID PHASE SEPARATION
No full textThesis (Ph.D.)--Michigan State University. Physics - Doctor of Philosophy, 2025To investigate protein behavior in vitro it is important to mimic the cellular environment. Given the high densities of ~ 400 mg/mL and the large number of a variety of macromolecules present in cells, reproducing this complex crowded environment in vitro has been a difficult task. Most of the time crowding is achieved through synthetic polymers such as polyethylene glycol (PEG) or concentrating the protein of interest itself which can underestimate interactions and hide the true protein behavior. We expect condensates formed through liquid-liquid phase separation (LLPS) to be a better platform to study proteins or RNA such as scaffold-client condensate systems which can incorporate a variety of macromolecules under physiological conditions. In this work we study such condensate environments and investigate protein behavior.We investigated a short polymer system of the RNA poly-adenine with the peptide RGRGG to understand the length dependance of LLPS and its underlying thermodynamics. Results showed that the length dependance of LLPS is primarily driven by the entropy of confinement. To study macromolecular behavior in vitro using condensates as a crowded platform, we introduce Trp-Cys quenching as a technique to measure the dynamics of intrinsically disordered proteins (IDPs) in condensates. We were able to successfully calculate the intra-molecular diffusion of \u3b1-synuclein (\u3b1-syn) in RLP condensates, and the protein appeared to be highly dynamic in the condensed phase showing only ~ 50 % slowdown in intra-molecular diffusion compared to its monomeric state in the dilute solution even though the concentration in condensates was ~ 300 times high. We also developed the Trp-Cys quenching technique to characterize transient inter-molecular interactions of proteins under crowded conditions. Using Villin variants and drkN SH3 domain with Protein G as the crowder the technique was able to capture the difference between long-range repulsive and attractive interactions, the strength of short-range interactions, concentration variations and interaction preference for different sites. Furthermore, we investigated the early-stage aggregation of O-GlcNAcylated \u3b1-synuclein at two different sites T72 and S87. Results indicated that while glycosylation at T72 can suppress early-stage aggregation S87 can promote it. We were able to hypothesize that this distinction is because the most common transient interactions for these two sites are different.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
The newsletter of the Golf Course Superintendents Association of New England, Inc. (2025 January/February)
No full textEnabling a Multi-Pronged Socio-technical Approach to Address Automotive Cybersecurity
Get PDFThesis (Ph.D.)--Michigan State University. Computer Science - Doctor of Philosophy, 2025The increase of inward-facing and outward-facing communication used by modern vehicles with automated features expands the breadth and depth of automotive cybersecurity vulnerabilities. The prominent role that human behavior plays in the lifetime of a vehicle creates a need for social and human-based factors to be considered in tandem with the technical factors when addressing cybersecurity. Specifically, in collaboration with researchers from criminology and the automotive industry, we integrate foundations of crime theory, human factors, and model-driven engineering to develop three complementary automotive cybersecurity prevention strategies, where they differ in the balance between technical and social emphasis, both in terms of solution strategies and the targeted stakeholders. We start with a stakeholder-aware threat assessment to analyze automotive systems for vulnerabilities and solutions across the spectrum of stakeholders using the vehicle. In addition to identifying attack surfaces, this threat assessment includes relevant human-focused information, such as type of access needed by attacker (e.g., physical or remote; time needed to complete attack), attacker background knowledge, and impact on human safety. This threat assessment is used to inform all three of our approaches to automotive cybersecurity. First, we developed a set of technical automotive cybersecurity design patterns (i.e., reusable designs for specific cybersecurity problems), targeting the technical stakeholder group. Second, leveraging situational crime prevention strategies, we developed a configurable situational crime prevention framework for automotive cybersecurity where we consider both state of the art and state of the practice strategies to address vulnerabilities. Targeted stakeholders include dealerships, OEM's, and developers. Finally, we developed socio-technical design patterns that provide reusable solution strategies that engage the broader community to address automotive cybersecurity. Example stakeholders include third party vendors, automotive hobbyists, and white-hat attackers. These three strategies provide reusable solutions to be realized by a spectrum of technical and social-based activities to address automotive cybersecurity, which engages the broader community, thus increasing the overall impact and societal benefits. This dissertation takes an interdisciplinary approach to address automotive cybersecurity where we synergistically combine cybercrime theory, human factors, and technical solutions to develop reusable prevention and detection techniques.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
Examining Policy-Related Issues and Their Effect on Labor Dynamics and the Supply Chain
Get PDFThesis (Ph.D.)--Michigan State University. Business Administration -Logistics - Doctor of Philosophy, 2025This dissertation explores labor as an essential component of supply chain operations. Collectively, these three essays contribute to the domains of labor economics, supply chain management, and public policy, demonstrating that employment structures, labor market responses, and inter-industry dynamics are sensitive to regulatory environments and institutional constraints. Methodologically, this dissertation leverages robust causal identification strategies, including synthetic controls, natural experiments, and difference-in-differences, to establish strong causal inference. Theoretically, it extends economic property rights frameworks and supply chain spillover models to account for legal frictions and institutional change. For scholars, it offers integrative frameworks to study firm boundary decisions and policy-induced labor effects. For policymakers, the results highlight the heterogeneous and sometimes unintended consequences of regulatory interventions. For supply chain practitioners, the research provides insight into labor availability, governance structures, and compliance challenges that influence strategic sourcing and workforce management.The first essay (see Chapter 2) examines the consequences of California\u2019s Assembly Bill 5 (AB5), a landmark law addressing employee misclassification. Using a synthetic control method to identify causal impacts on employment dynamics in the trucking industry, I find a sharp decline in independent contractors (IC) and the shift toward vertically integrated employment models. This transformation is framed through Barzel and Allen\u2019s (2023) lens of property rights theory, whereby I explore how legal property rights cascade to impact economic property rights. The findings reveal that AB5 triggered significant firm-level adjustments, particularly among larger carriers and intermodal drayage operators. The study contributes to organizational theory by offering a unique temporal setting for institutionalization and firm boundary decisions and advancing a unified theoretical framework for organizational structures. The second essay (see Chapter 3) examines the local labor market effects of large multinational plants, termed \u201cMillion Dollar Plants\u201d (MDPs), on employment in ancillary sectors, specifically transportation and warehousing. Leveraging a difference-in-differences design, the study compares \u201cwinning\u201d counties that secure MDPs with \u201crunner-up\u201d counties, controlling for unobservable factors. This work highlights a surprising cannibalizing effect on local labor, underscoring the complex interplay between labor market dynamics and supply chain operations. Contrary to expectations, average spillover effects on local logistics employment are muted or negative but were found to be moderated by plant size. Higher-paying opportunities in transportation or manufacturing industries likely draw labor away from warehousing for larger MDPs. This study contributes by identifying boundary conditions to contextualize the direction of labor spillovers for transportation and warehousing industries through an additional perspective of county-level employment. These findings challenge conventional assumptions about regional economic development and underscore the nuanced dynamics of labor redistribution across industries. The third essay examines the labor market consequences of the early termination of enhanced federal unemployment insurance (UI) benefits during the COVID-19 recovery. Using border discontinuities between states that ended benefits early and those that did not, I conduct a county-level analysis. The results are heterogeneous across temporal and regional dimensions, concentrated in goods-producing sectors with energy fracking activity. While the policy had limited immediate impact, it highlights the broader context of mechanisms in play during economic recovery. This essay contributes to conflicting empirical findings in pandemic recovery and debates on optimal unemployment policy and macro-labor responsiveness.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references