Chapter 1:

Inspired by the political events that followed after the sovereign debt crisis in Greece post 2009, I develop an overlapping generations model with aggregate and idiosyncratic shocks to analyze agent's decisions if each had a vote in whether the country should default or not. The hypothetical economy where agents vote to default almost became a reality in 2015 when Prime Minister of Greece asked the voting population whether the country should remain in the bailout program through a referendum. Model results exhibit similar patterns as the Greek referendum with the young and less wealthy more inclined to vote for default.

Chapter 2:

We develop a theoretical model to highlight a previously

unexplored mechanism of price discovery: relative minimum price

increments for equivalent assets trading on distinct financial

exchanges. Although conventional wisdom dictates that futures

market assets lead equities equivalents in terms of price

formation, our model predicts that the opposite should be true

when particular relative price conditions hold for the bids and

offers of each asset. We develop a new empirical measure of price

discovery which is suited to asynchronous, high-frequency

transaction and quotation data, and apply it to the highly liquid

E-mini/SPY pair in order to test the predictions of the

model. Empirical evidence strongly supports the model and further

demonstrates that relative minimum contract size plays an

additional role in the formation of prices.

Chapter 3:

United States population has increasingly become older. The aging is expected to continue as life expectancy increases, more baby boomers reach retirement age and birth rate declines. These demographic changes have had significant impact on the solvency of the Social Security Trust Fund. Social Security Administration projects the fund's insolvency around 2035. Given the imminent insolvency, policies such as increasing eligibility age and expanding the tax base have been proposed. These policies are usually analyzed using many period OLG model with a hump-shaped age-dependent productivity profile. We believe this profile is dynamic as the population itself. We incorporate the dynamic age-dependent profile in an OLG framework in a closer look at insolvency of the Social Security Trust Fund.

Natural filamentous shaped biomolecules utilize their physical shape and chemical functionality to optimize and achieve hierarchical structures. They use weak interaction such as hydrogen bonds, hydrophobic interaction, charge-charge interaction, van der Waals force and so on. The major advantage of using weak interactions is that they enable biomolecules to adopt the reversible assembly and reorganization of the structures. In my work, I use M13 bacteriophage (M13 phage) to investigate how intrinsic molecular interaction affect phase transition, self-assembly process, and hierarchical structure formation. I used genetically engineered phage with the peptide motif of elastin-like polypeptide (ELP). Insertion of target sequence of peptide on the surface of M13 phage can endow functionality on the M13 phage. Firstly, I investigated novel liquid crystalline transition upon stimuli application. Counterintuitive liquid crystalline order increase upon heating was investigated with engineered M13 phage. Secondly, molecular crowding environment make M13 phage forming long-range ordered smectic structures. The addition of non-interacting colloidal particles provides depletion force to phage and accelerate their assembly. Due to the intrinsic molecular interaction engineered phage, I investigated time dependent structure evolution process. Last, I applied ELP as interacting colloids to engineered phage. Because ELP possesses same peptide motif, they could have interaction despite different molecular shape. Unlike the mixture system of phage and non-interacting colloids, engineered phage and ELP mixture system showed dual phase transition and helical fiber formation. Furthermore, I could turn off and on the depletion force by controlling temperature. I show that our novel liquid crystalline phase transition is based on the attractive interaction. Through my dissertation, I hope the combination of functionality of peptide and liquid crystal molecule could convey the insight for molecular design and development of hierarchical structure formation.

Bioelectricity is generated by a wide spectrum of living organisms, ranging from single-celled entities to intricate multicellular organisms. These organisms have evolved intricate mechanisms to regulate and manage electrical activity. The understanding and controlling of bioelectricity hold the potential to yield diverse bioelectrical applications. However, comprehending bioelectrical systems using conventional organic/inorganic materials remains challenging because these materials lack the inherent complexity and adaptability that make replication difficult, limiting their capacity for modification and customization. Biological systems are highly complex, comprising various components such as nucleic acids, proteins, and tissues that display high specificity and selectivity in their interactions and processes. This complexity and heterogeneity hinder the accurate replication or mimicry of biological processes at the molecular level. Viruses, being submicroscopic infectious entities, serve as powerful tools for advancing our understanding of fundamental biological systems. Using the M13 phage as a model system due to its simple structure, versatile, biocompatible, and massively replicable characteristics, the structure-function relationship of bioelectricity is studied. This thesis explores the responsive electrical properties of viruses to external stimuli such as friction, mechanical stress, heat, and chemical environments. It examines how genetic modifications of viruses alter their structural and electrical properties, introducing practical virus-based bioelectrical applications. By using the M13 phage as a model system for investigating bioelectricity, this research aims to offer valuable insights into the design and development of innovative bioelectrical applications, bridging the gap between conventional materials and biological systems.

Smart biomaterials that can actively respond to and interact with their environment are sought after for regenerative medicine, therapeutic delivery, sensing, and actuation. Polymer-nanoparticle hybrids are a promising class of smart materials, but thus far the choice of polymers has predominantly been chemically synthesized ones. In contrast, natural tissues commonly utilize proteins to interface with nanoparticles and provide smart functionalities. Inspired by nature, this dissertation describes the development of genetically engineered, protein-based polymers (PBPs) for use as components of smart, polymer-nanoparticle hybrids. Specifically, elastin-like polypeptides (ELPs), a class of thermoresponsive PBPs, were utilized to functionalize two nanoparticles.

First, an improved method for synthesizing PBP genes was developed. Crafting new PBPs is limited by the ease with which their genes can be engineered. The new method utilizes a specific architecture of restriction enzymes to address some of the drawbacks of previous methods and was used to efficiently and accurately produce ELP genes.

Next, ELPs were engineered to display biomimetic, bone mineral-binding peptides and their effect on therapeutic bone cements was investigated. Bones are mechanically robust, composites composed predominantly of proteins and nanocrystalline mineral. In contrast, bone cements are brittle and do not contain organic materials. Composites of mineral-binding ELPs and cement had significantly improved strength. Furthermore, the injectability and washout resistance of cements were improved as a result of the ELP's thermoresponsive behavior.

Finally, photoresponsive composites were created by engineering ELPs to display graphene-binding peptides. Graphene-derived nanoparticles (GNs) exhibit unique mechanical, electrical, and optical properties but are difficult to integrate into biological systems due to their hydrophobic nature. The engineered ELPs non-covalently bound to GNs and the resulting ELP-GN hybrids exhibited increased colloidal stability and a reversible temperature-controlled aggregation behavior. The ability of GNs to convert near-infrared light to heat was exploited in order to remotely induce aggregation of ELP-GN hybrids in solution and to induce rapid, site-specific actuation of ELP-GN composite hydrogels. Finally, cell adhesion on ELP-functionalized graphene was enhanced by genetic addition of integrin-binding peptide motifs.

These studies demonstrate that PBPs can be tailored to interact with nanoparticles of choice and can provide stimuli-responsive and bioactive properties to biologically relevant nanoparticles. Hybrid materials of PBPs and nanoparticles are, therefore, well suited for biotechnological applications which require smart behavior.

Abstract

The image of a hero reflects the desires, ideals and dreams of the people of a given time. ¡°It is in times of emergency that heroes are looked for, and found,¡± as Lucy Huges-Hallett pointed out. In times of war or social disorder, people look for someone who can save them from chaos. That is why these intellectuals of the colonial period gathered to find heroes from the past. If the environment is what creates necessity for a hero, what does the type of heroic figures tell us about the past or present?

The role of heroes in premodern Korean literature is similar to what Ruhlmann depicts. They ¡°embody current values and ideals¡± which can be understood in part as Confucianism, and they also ¡°convey a powerful image of the conflicting forces at work in the society of their time.¡± Furthermore, if, as Frederic Jameson argued in The Political Unconscious, narratives are ¡°socially symbolic acts,¡± then works of popular fiction may be seen as texts representing an ¡°individual parole or utterance¡± of ¡°collective and class discourses,¡± since such works simultaneously represent perspectives of writers and readers, the literati and commoners in the Chosŏn period (1392-1897).

By investigating heroes in premodern literature, we can find an answer to the question of ¡®who created which heroes for whom?¡¯ Furthermore, it is also important to look at any differences of heroic images within the same period to see how they may vary depending on social class, gender, and region. The answer to these questions tells us about current values and ideas, in addition to class/gender conflicts of the time. This dissertation will specifically focus on Korean hero fiction (yŏng¡¯ung sosŏl; Ó¢ÐÛСÕf) in the late Chosŏn period, a genre considered to be most ¡°influenced¡± by Chinese works.

Hero fiction was the most popular literary genre in premodern Korea. For that reason, we can consider writing/reading/circulating hero fiction as a reflection of contemporary popular culture. John Storey defines popular culture in five different ways. First, ¡°popular culture is simply culture that is widely favored or well liked by many people.¡± Second, ¡°it is the culture that is left over after we have decided what is high culture.¡± Third, popular culture is ¡°a mass culture.¡± In this case its focus is on commercial culture. Fourth, ¡°popular culture is the culture that originates from the people.¡± Lastly, it is ¡°a site of struggle between the ¡®resistance¡¯ of subordinate groups and forces of ¡®incorporation¡¯ operating in the interests of dominant groups.¡±

Using Storey¡¯s five definitions of popular culture, I will examine four major works of hero fiction: A Dreams of Nine Clouds (Kuun mong) Record of Black Dragon Year (Imjin rok) and Tale of Hong Kyewŏl (Hong Kyewŏl chŏn). By examining these three hero fictions, we will be able to see how popular culture functions against dominant elite culture in the late Chosŏn period. This kind of study will be a foundation for examining the cultural, social and literary characteristics of that time.

This dissertation proposes longitudinal growth curve cognitive diagnosis models (GC-CDM) to incorporate learning over time into the cognitive assessment framework. The approach was motivated by higher-order latent trait models (de la Torre & Douglas, 2004), which define a higher-order continuous latent trait that affects all the latent skills. The higher-order latent trait can be viewed as the more broadly defined general ability; and the skills can be viewed as the specific knowledge arising from the higher-order latent trait. GC-CDMs trace changes in the higher-order latent traits over time by using latent growth curve model with respondent-specific random intercept and random slope of time, and simultaneously trace students' skill mastery through the CDM measurement model.

GC-CDMs are estimated using marginal maximum likelihood (MML) estimation in Mplus. Relevant issues for estimating GC-CDMs are addressed, e.g., the high-dimensional computation problem, model specification for the relationship between the higher-order latent trait and the multiple skills, and model identification. In simulation studies, we use the DINA measurement model, and examine parameter recovery of the GC-DINA model under differing conditions. Particularly, the effects of the design of the Q-matrix, the number of respondents and the number of time points are discussed. Overall, MML estimation in Mplus shows good parameter recovery; especially, the average growth, which is the parameter of most interest, is well estimated in all conditions. We also illustrate the application of the GC-DINA model to real data using two datasets from multi-wave experiments designed to assess the effects of the Enhanced Anchored Instruction (EAI; Bottge et al., 2003) on mathematics achievement. In addition, the GC-DINA model is compared to the latent transition analysis DINA model (LTA-DINA) (Li et al., 2016; Kaya & Leite, 2016) and a longitudinal item response theory (IRT) model (Andersen, 1985) using a simulated data. The results suggest that the GC-DINA model and the LTA-DINA model are similar in terms of the predicted skill mastery; and the GC-DINA model and the longitudinal IRT model are similar in terms of the predicted higher-order latent trait.

How should monetary policy deal with endogenous stock and bond market fluctuations? This dissertation focuses on the interaction among uncertainty arising from financial markets, risk- premium (and term-premium), and the business cycle. The main objective is to study various effective monetary policy responses for stabilization purposes.

The first chapter offers a non-linear version of the standard New-Keynesian framework, in which I provide an illustration of how the consideration of the first-order effects of endogenous and time-varying aggregate risks changes the business cycle dynamics. With conventional monetary policy rules, my non-linear characterization of the solution features interesting potentials for the sunspot equilibria arising from the aggregate business cycle volatility. I provide a new monetary policy rule that restores model determinacy and achieves the economy’s full stabilization again. The entire results rely on the interaction between aggregate consumption demand and the economy’s aggregate risk through the famous precautionary savings channel. This result is novel.

In the second chapter, I develop a more full-fledged New-Keynesian framework with active stock markets that features a potential for self-fulfilling financial uncertainty arising from its interaction with risk-premium, wealth, and aggregate demand. The model remains tractable, providing closed-form expressions for higher-order moments tied to the financial uncertainty and their relations to the rest of the economy. I re-examine the optimality of conventional monetary policy rules and show that the ‘Taylor principle’ no longer guarantees determinacy, with sunspots in aggregate financial volatility not precluded by aggressive targeting of inflation and output gap alone. I then characterize the joint dynamic evolution of financial volatility, risk-premium, asset prices, and the business cycle in a rational expectations equilibrium with sunspots, and uncover that variations in financial uncertainty generate reasonable crises and booms along the business cycle that are consistent with my empirical estimates based on the US data. As this pitfall of the traditional policy rules lies in their inability to target the expected return on aggregate wealth, the relevant rate in stochastic environments, I then propose a ‘generalized’ Taylor rule that targets risk-premium and asset price, and describe the necessary conditions that restore determinacy and achieve the ultra-divine coincidence: the joint stabilization of inflation, output gap, and risk-premium. Finally, I revisit the zero lower bound (ZLB) and show it amplifies the duration, severity, and welfare costs of fluctuations in financial volatility. Alternative policies such as forward guidance reduce these welfare costs on average, but risk worsening economic situations with a non-zero probability, raising interesting trade-offs for policymakers.

The failure of conventional monetary policy to stabilize the economy at the zero-lower bound (ZLB) has made unconventional interventions more prevalent in recent times, which calls for a new macroeconomic framework for properly analyzing these policies. In the third chapter, I develop a New-Keynesian framework that incorporates the term-structure of financial markets and an active role for government and central bank’s balance sheet size and composition. I show that financial market segmentation and the household’s endogenous portfolio reallocation are crucial features to properly understand the effects of Large-Scale Asset Purchase (LSAP) programs. I propose a new micro-foundation based on imperfect information about expected future asset returns that easily accommodates distinct degrees of market segmentation across asset classes and maturities, while providing intuitive and tractable expressions for the household’s portfolio shares. My analysis reveals that government’s issuance of risk-less bonds stimulates the economy when conventional monetary policy is constrained at the ZLB, which is consistent with the literature on the so-called “safe-asset shortage problems". I also find that central bank’s bond purchases across different maturities act as a major determinant of the level and slope of the term-structure, and yield-curve- control (YCC) policies that actively manipulate long-term yields are powerful in terms of stabilization both during normal times and at the ZLB. As a drawback, YCC policies increase the likelihood of ZLB episodes and their durations, thereby locking the central bank in a position in which the short-term rate is less useful as a policy tool.