UC Irvine

Time series econometrics is essential to empirical studies in macroeconomics, finance, and many other areas.While the canonical models in this literature are small, parametric, and linear, there is growing interest in models in which the data generating process is either nonlinear or of a flexible, adaptive form. This dissertation proposes several new models and techniques in the area of flexible and nonlinear time series econometrics.

Chapter 1 proposes a novel methodology for determining the specification of factor-augmentedvector autoregression (FAVAR) models. Without strong a priori beliefs about the set of possible models, the complexity of the problem renders traditional model selection techniques infeasible. By contrast, my proposed solution only requires the estimation of a single model. This makes the process easy to scale in both the cross-sectional and time series dimensions. An efficient optimization algorithm for model estimation is developed. Monte Carlo studies show the technique to be highly effective in small samples, even in the presence of a low signal-to-noise ratio and missing data. Applications to large datasets of monthly and quarterly U.S. macroeconomic variables identify observed factors not normally considered in the FAVAR literature. The methodology is then used to analyze the asset-pricing model of Fama and French (1993). I find that their constructed factors for firm size and book-to-market equity ratio are likely observed components, but excess market return is not.

Chapter 2 proposes a regime-switching linear model with time-varying transition probabilities,endogenous switching, and a nonparametric error distribution. The last two qualities are achieved by letting the conditional mean of the normalized observation errors be a potentially nonlinear function of the errors in the state equation. We demonstrate that this specification permits a very flexible marginal distribution for the observation error. A Markov Chain Monte Carlo algorithm for sampling from the posterior distribution of parameters is developed. A simulation study demonstrates that existing parametric switching models yield biased parameter estimates when the data is generated by a model with nonlinear endogenous switching. We apply the model to US quarterly output growth. The proposed model is shown to fit the data better than parametric switching models.

Count data models are at the core of a large and diverse empirical literature in the socialand natural sciences. A key component in this class of models is the mean function, which defines the relationship between the covariates and the conditional expectation of the count process. Chapter 3 considers a general approach for representing the mean function that is adaptable, tractable, and dispenses with problematic facets of count data models such as explosive covariate effects and restrictive time series properties. The methodology is broadly applicable in cross-sectional, longitudinal, and time-series settings, with likelihood-based, generalized linear, copula and other models. We provide theoretical results that distinguish our methodology from existing work and implement it in two examples that demonstrate its relevance and practical appeal.

Prior research has illuminated the significance of the column base connections on the seismic performance of structural systems. Among the various configurations adopted worldwide, this dissertation predominantly focuses on stiffened column base (SCB) connections. The SCBs are the common practice in countries where the fabrication of thick plates for exposed column base (ECB) connections and the execution procedure of embedded column bases are challenging. The SCB configuration is characterized by integrating stiffeners atop an exposed base plate. The formed stiffened panels effectively reduce the required base plate thickness to resist the desired flexural strength compared to that demanded by comparable ECB configurations. Despite their application in low- to high-rise structures, empirical investigation on their hysteretic behavior is scarce, and their design methodologies either stem from theoretical principles or adaptations of existing ECB design approaches. Nonetheless, their distinctive features — the combination of rigid nature and thin base plate, alongside the incorporation of multi-row arrangement — notably diverge from those of ECBs. To bridge the gap between theory and practice, this dissertation investigates the hysteretic characteristics of SCB connections, both experimentally and analytically. The research effort presented herein first conducts an experimental testing campaign on SCBs to document the qualitative observations and quantitative outcomes of their responses to cyclic loadings. Four large-scale tests explore the impact of the inclusion of inner rods, construction features, and base plate thickness. The collected database provides the foundation to validate a virtual finite element (FE) framework. This robust simulation environment tackles the deficiency of mechanical evidence for the complex interactions between connection components. This study sheds light on the disregarded significance of the friction between anchor rods and concrete on the internal characteristics of hysteretic curves. The activated friction is attributed to the developed compressive forces in the anchor rods leading to their expansion. The observation of a punched foundation after experiments motivated an FE study to quantify the impact of the incorporation and location of leveling nuts on the behavior and hysteretic energy dissipation of column bases. Following this, SCB specimens featuring diverse anchor rod arrangements, axial loading levels, and stiffener layouts are simulated to generate a comprehensive dataset for subsequent evaluations. Through these sophisticated simulations, this work elucidates the hysteretic characteristics of SCBs, evaluates the efficiency of current design approaches in predicting yield strength, identifies potential unconservative design practices, and proposes a numerical method for predicting SCB connection behavior. The limitations of the project are outlined. The perspective derived will contribute to developing system-level analytical models to explore SCB's impact on structural performance.

In software engineering, a whiteboard is a commonly used tool. One particular setting is that of software developers using a whiteboard when they hold software design meetings. They do so because whiteboards offer a fluid and flexible drawing experience. At the same time, the simplicity of the interaction on the physical whiteboard (only drawing and erasing) can be a weakness. Researchers in the past have proposed different variations of whiteboards to make up for this weakness, but to date they have not addressed the fact that novices are prone to becoming lost in their design work precisely because of the fluidity and flexibility. This thesis presents Tabbie, an electronic whiteboard tool with preloaded tabs that are meant to guide novices when they engage in design work. To assess Tabbie, I performed a preliminary experiment with 15 university students designing a ride-sharing service. I present preliminary results that the existence of tabs can be helpful to novices when theywork on software design.

Debates over paid peering and usage fees have expanded from the United States to Europe and South Korea. ISPs argue that content providers should pay fees based on the amount of downstream traffic they generate. In contrast, content providers contend that customers already pay ISPs for delivering the content they request, and therefore that peering agreements should be settlement-free. The issue has arisen in debates in the United States, Europe, and South Korea over net neutrality, universal service, and infrastructure funding. Regulatory entities are considering whether to regulate peering prices and/or impose usage fees. A key part of the debate concerns whether the market determines the socially beneficial peering price, and if not, how much of a difference there is between the socially beneficial peering price and the market-determined peering price. Our objective here is to understand the range from a cost-based peering price to a profit-maximizing peering price.

First, we determine an ISP’s cost for directly peering with a content provider, by analyzing the incremental cost for transporting the content provider’s traffic when it directly peers with the ISP versus when it sends its traffic through a transit provider. Next, we determine the peering price that maximizes an ISP’s profit using a two-sided market model in which a profit-maximizing ISP determines broadband prices and the peering price, and in which content providers determine their service prices based on the peering price. These prices establish a range if the peering price is unregulated, from the cost-based peering price (at the low end) to the profit-maximizing peering price (at the high end). Regulatory oversight of peering prices may be warranted when there is a substantial difference between cost-based and profit-maximizing prices.

Finally, we re-examined the arguments put forth by large ISPs and large content providers. Our results show that settlement-free peering is warranted if a content provider or transit provider provides sufficient localization of exchanged traffic. Traffic is sufficiently localized if: (1) they interconnect at a reasonable number of interconnection points, (2) the locations of these interconnection points span the country, and (3) the proportion of traffic that is exchanged at an interconnection point that is relatively close to the end user is sufficiently high.

Electronic health records (EHRs) have become a powerful resource for studying health outcomes. In time-to-event settings, EHRs are usually subject to interval censoring on the true time of the event. It is common to consider the outcome to be the time of diagnosis. Standard survival analysis tools for right-censored data, such as the Cox proportional hazards model, are commonly used to estimate covariate associations with the time-to-event in such settings. Patients may, however, have access to multiple health care providers across different systems. If patients seek care from external health systems (a phenomenon we call system migration), the diagnosis times within the observed system may be erroneously prolonged. No work has considered the performance of the Cox model under system migration. In this dissertation, we show that system migration related to the outcome of interest results in biased estimates of hazard ratios from the Cox model. We develop an extension to the Cox model that adjusts for system migration by 1) estimating the probability of system migration for each patient and 2) uses multiple imputation to adjust diagnosis times for patients identified as migrating across systems. A vital part of this method involves developing a prediction model from patient-specific system usage patterns for estimating the probability of system migration. To improve prediction assessment, we develop an estimator for time-dependent sensitivity and specificity in the recurrent event setting with unbalanced data across subpopulations. Finally, we consider the choice of time scales for assessing the relative risk of disease diagnosis. We compare the appropriateness of two commonly assumed time scales that define risk sets in the Cox model: the age time scale and the time-on-study time scale. Previous research has suggested that the age time scale, corresponding to birth as a time origin, is most appropriate for epidemiological studies. However, simulation studies have suggested that the time-on-study time scale with covariate adjustment for baseline age is more robust to misspecification of the time scale. We investigate the performance of the Cox model under each time scale under varying degrees of model misspecification and further assess the robustness of each approach when modeling time-varying covariates.

Despite the extensive literature about urban places in the United States, rural places are frequently overlooked in scholarly discourse. Society often romanticizes rural places as idyllic, agrarian, and untainted spaces (Bell, 1992, 2007; Cloke, 2006; Halfacree, 1995; Theodori & Willits, 2019; Willits et al., 1990; Willits & Luloff, 1995). However, rural communities confront a multitude of social challenges, including pervasive poverty, limited educational attainment, and pervasive alcohol and drug challenges (Brown & Lichter, 2004; Garcia, 2008; Lichter & Brown, 2011; Roscigno et al., 2006; Van Gundy, 2006). While crime may occur less frequently in these areas, certain rural places experience higher rates of violent offenses compared to some urban counterparts (Morgan & Thompson, 2021). Furthermore, recent assessments have shed light on the disconcerting reality that rural regions have evolved into focal sites of mass incarceration, contributing significantly to the escalating number of people admitted to jails across the United States (Vera Institute of Justice, 2020; Kang-Brown & Subramanian, 2017; Eason, Zucker, & Wildeman, 2017). Notwithstanding existing research’s careful consideration of the distinctive nature of rural law enforcement and conceptions of rurality, a tendency exists to occasionally overlook the stigmatization and the profound ramifications it engenders in rural communities (an exception Eason, 2017b). To broaden our understanding of rural Latinx communities, this research assesses El Valle, a rural Hispanic community in New Mexico. Drawing on archives, interviews, and participant observation and a case study method (Yin, 2003), I investigate the intricate interplay between place, stigma, and identity, aiming to discern the consequences of territorial stigma in El Valle. Specifically, I seek to illuminate how territorial stigma affects individuals and shapes their identities. Furthermore, I explore the strategies that El Valle residents employ to navigate, resist, and shield themselves from the negative reputation attached to their community. Lastly, I delve into the experiences of practitioners in El Valle, shedding light on the perspectives of practitioners about the people they encounter in their work. Altogether, I argue that the interplay between news media, the state, and community members serves as a form of power to exercise domination, discipline, and social control over this community.

Alzheimer’s disease is a progressive form of dementia with no effective treatments. Episodic memory deficits are a defining cognitive symptom of Alzheimer’s disease, which may be related to changes in the medial temporal lobes (MTL). The MTL facilitates episodic memory function and is particularly vulnerable to Alzheimer’s disease pathology. Both sleep and physical activity are linked to episodic memory function, including pattern separation operations reliant on the MTL. Evidence in young adults suggests that sleep and exercise are each independently linked to mnemonic discrimination (behavioral correlate of pattern separation), but it is unclear whether they interact to do so, and through what mechanisms. Whether these relationships are altered in older adults at-risk for Alzheimer’s disease is also unknown. To fill this knowledge gap, a series of studies were conducted. In Chapter 2, self-report measurements of sleep, physical activity, and cognitive function were used to statistically model the mediating effect of sleep in the physical activity-cognition relationship. In Chapters 3 and 4, high-density electroencephalography was recorded during overnight sleep to measure the expression and coupling of non-rapid eye movement (NREM) sleep oscillations, a memory task assessing mnemonic discrimination was administered prior to and following sleep to measure sleep-dependent memory consolidation, and questionnaire data assessing physical activity frequency and duration was collected from 36 older adults. High-resolution resting-state functional magnetic resonance imaging data previously collected from this same participant cohort was analyzed to derive measures of resting-state network modularity and MTL centrality. Chapters 3 and 4 addressed three specific aims: (1) whether local expression and coupling of NREM sleep oscillations are associated with sleep-dependent memory consolidation (Chapter 3), (2) whether network modularity and measures of MTL centrality are associated with sleep-dependent memory consolidation (Chapter 3), and (3) whether physical activity is associated with these same mechanisms (Chapter 4). This research provides novel insights into the neurobiological mechanisms supporting the relationships among sleep, physical activity, and memory consolidation in older adults. Findings from this dissertation could guide prospective physical activity and sleep-based interventional studies to improve memory function and inform public health recommendations to reduce Alzheimer’s disease risk by underscoring the importance of sleep.

The Free space optical (FSO) communication has long been considered a promising solution for high-speed broadband data transfer. A conventional FSO receiver consisting of a focusing lens and a small high-speed detector works efficiently for a limited range of angles of arrival (AoA). This makes the optical link vulnerable to AoA fluctuations jitter. Even with a dedicated Pointing, Acquisition, and Tracking (PAT) system, residual jitter with variance in the range of microradian is unavoidable in FSO communication. The jitter causes BER fluctuations over a long time. Moreover, multi-beam optical communication in which one receiver needs to connect with multiple transmitters dispersed in 3D space at the same time cannot be implemented with the conventional receiver. This thesis presents two receiver designs based on metalenses that can offer solutions for these problems. To reduce the AoA fluctuation, a metalens is introduced at the focal plane of the bulk aperture lens of a conventional receiver. The phase profile of the lens is optimized to allow efficient capture of beams with AoAs as large as 2.5mrad. This is a significant improvement over a conventional receiver without metalens, which can capture only 195μrad with the same efficiency. For multi-beam communication, a two-metalens receiver system with optimized phase profiles is proposed. A proof-of-concept three-beam communication link is demonstrated in which the maximum AoA of 2° can be captured with 67% efficiency. This shows 35X improvement over conventional systems with a single detector in terms of acceptable AoA. The performances of the proposed receivers are analyzed with diffractive optics calculation. Metalens unit cells at two different wavelengths (1μm and 1.55 μm) are presented in this thesis. Full metalens systems are created based on the phase response of unit cells with varying diameters and simulated in Lumerical and COSMSOL. The simulation result validates the efficiency of the proposed receivers. When implemented, the proposed receiver will increase the capacity of communication links as well as maintain the same capacity over a long period of time. The proposed method can further be used to design receiver modules for specific situations such as for CubeSat/ astrophysical observation.

This dissertation consists of three essays on empirical financial economics. The first essay, “External Litigation Risk and Corporate ES Performance: Evidence from Federal Judge Ideology”, explores how firms’ environmental and social (ES) performance are affected by external ES litigation risk, proxied by judge political ideology. The second essay, “Local Environmental Beliefs and Corporate Environmental Performance”, which was co-authored with Yuhai Xuan and Hong Wu, investigates the effect of local environmental beliefs on US establishments’ environmental performance and on firms’ pollution reallocation decisions. The third essay, “Information on Collateral Value and Bank Mortgage Lending”, studies the US residential property market and the effect of collateral information advantages on banks’ lending decisions.

Multispectral materials are of great need in advanced applications in electronics, camouflage, personal clothing, and space missions. Consequently, substantial effort has been made over the years to design materials of complex functionalities enabling them to perform within either one or both visible and infrared electromagnetic ranges. Nonetheless, many of these multispectral materials are limited by their scale and restricted tunability as well as challenges related to their functionalities in different wavelength ranges forcing a settlement on compromised properties. To address these challenges, we drew inspiration from cephalopods, the marine masters of light. Their astounding ability to dynamically tune their optical appearance is possible due to the complex skin structure composed of chromatophores and iridophores splotches providing pigmentary and structural coloration, respectively. From these, we first developed large-area chromatophore-inspired adaptive infrared and thermoregulatory materials featuring on-demand infrared transmittance modulation for over 20-fold accompanied by heat flux by over 30W m−2¬ when mechanically actuated. Next, we modified our chromatophore-inspired composite materials and broadened their wavelength functionality by enhancing them with visible wavelength-selective, splotch-inspired structures and obtaining hybrid multispectral composite materials of maintained infrared transmittance modulation of over 20-fold and additional visible reflectance modulation of over 9-fold upon the mechanical actuation. Altogether, our findings demonstrate a successful design and fabrication of multispectral thermoregulatory materials with tunable functionalities which can find application in advanced systems such as wearable electronics, thermal-management systems, smart windows, and multispectral camouflage.