Stochastic Trade Networks

This paper develops a simple network model to describe the dynamic of the intensive and extensive margin of international trade flows. The result is achieved by means of the combination of two mechanisms of proportional growth: the first (discrete) determines the formation of trade links, the second (continuous) governs trade intensity. We show that our setup is able to simultaneously match a large number of empirical regularities, such as the fraction of zero trade flows across pairs of countries or the high concentration of trade with respect to both products and destinations. Our findings suggest that stylized facts are strongly interconnected across different levels of aggregation of trade data , so that a unifying explanation is called for. By incorporating stochastic elements into standard trade models we can improve their ability to explain relevant facts about world trade

Complexity in Economic and Social Systems

There is no term that better describes the essential features of human society than complexity. On various levels, from the decision-making processes of individuals, through to the interactions between individuals leading to the spontaneous formation of groups and social hierarchies, up to the collective, herding processes that reshape whole societies, all these features share the property of irreducibility, i.e., they require a holistic, multi-level approach formed by researchers from different disciplines. This Special Issue aims to collect research studies that, by exploiting the latest advances in physics, economics, complex networks, and data science, make a step towards understanding these economic and social systems. The majority of submissions are devoted to financial market analysis and modeling, including the stock and cryptocurrency markets in the COVID-19 pandemic, systemic risk quantification and control, wealth condensation, the innovation-related performance of companies, and more. Looking more at societies, there are papers that deal with regional development, land speculation, and the-fake news-fighting strategies, the issues which are of central interest in contemporary society. On top of this, one of the contributions proposes a new, improved complexity measure

Leveraging Policy for Renewable Energy Development in Industrialized Countries and Emerging Markets

Renewable energy has the ability to play a dominate role in addressing both rising energy demand and the need for sustainable growth. Various policy measures and incentives have aided its growth in both developed and developing countries. This dissertation analyzes existing policies and financial mechanisms used to encourage renewable energy development through three academic papers. I first propose the carbon revenue bond as a new financing tool to complement the environmental credit markets that exist in developed countries. Stochastic modeling techniques are used to simulate future credit prices and determine bond value. Use of the carbon revenue bond is illustrated through three examples of wind energy projects in the European, Australian and New Jersey markets. In the absence of mature markets in developing countries, I develop the strategic structure matrix as a new framework to explain the various effects of policy measures in order to better shape future policy design. By synthesizing previous literature on how organizations are able to affect the diffusion of a new technology, the strategic structure matrix is able to deepen understanding of how policy can influence renewable energy growth. The explanatory power of the framework is demonstrated through a case study on the different paces of wind power diffusion in five Indian states. Lastly, I evaluate the Clean Development Mechanism as a tool to encourage investment from developed nations for renewable infrastructure in developing countries. I create an agent-based model to simulate investment decisions under different improvements to the program, providing quantitative support for the effectiveness of some improvements over others. In addition to each paper's individual contributions, the findings collectively provide important implications for the future of renewable energy policy and its ability to support continued sustainable growth

Epidemic models for U.S. financial subprime mortgage crisis in 2008 influencing on Korean corporations

Department of Management EngineeringA financial crisis can spread like a contagious disease to both domestic sectors including demand market and foreign markets which are linked to one country with various aspects. This work mainly focuses on contagious phenomenon which is observed in Korean corporations enlisted in KOSPI & KOSDAQ index right after U.S financial shock in 2008. To set up the model, we use SIR epidemic model to detect epidemic dynamics in Korean corporations after shock. In addition, EDF model is also applied to analyze the degree of contagion within individual business. Using corporate fundamental data from KRX and FSS, including stock price, total market value, and current liabilities from Jun. 2008 to Jun. 2010, we observe contagious features resulted from U.S. financial crisis - EDFs are rising or show sustained level within infected corporations. We also presume parameters including contact rate and recovery rate to identify epidemic model of U.S. financial crisis which especially affected business sector in Korea. Further research is needed to identify the individual movement of certain sector or individual corporations from a view of agent-based model.ope

Optimization and Synthesis of Silver Nanoparticles Embedded Within a Porous Substrate for Raman Spectroscopy

Raman spectroscopy is a promising method for detection of a wide range of water contaminants. Raman spectroscopy’s growing list of applications relies upon signal enhancement achieved in recent years. A test strip or substrate designed to optimize Raman spectra, capable of withholding water and enhancing signal, would be a useful tool for applications including water quality tests. Signal enhancement may be achieved by the addition of silver nanoparticles (NPs) into a three-dimensional structure of cellulose nanofibers (CNF). The magnitude of signal enhancement may be related to nanoparticle size and morphology, and so control over the synthesis of silver nanoparticles could prove essential to this emerging technology. Particle diameter may be controlled by careful selection and concentration adjustment of the reducing agent in addition to varying the reaction’s duration. In addition to the resulting size, the reliability of the signal would rely upon its reproducibility, which would in turn be affected by the size distribution of nanoparticles produced, as well as their even dispersion within the test strip. To produce a nanoparticle engineered for use within a cellulose nanofiber substrate, a number of these parameters were investigated

Influence of silica nanoparticles on the surface properties of carbonate reservoirs

In the last decade, nanofluids-based techniques have shown tremendous promise in oil and gas industry. Nanofluids, dispersions of nanoparticles (NPs) in a base-fluid, have shown promises potentials in enhanced oil recovery (EOR), and carbon geosequestration projects. Based on the qualitative analysis, the study reveals that NPs, as a new EOR approach, offer applicable potentials and opportunities that can be implemented successfully at reservoir conditions and show better profits over conventional EOR techniques