Measuring Interdependence of Inflation Uncertainty

The unprecedented fiscal and monetary policy responses during the COVID-19 crisis have increased uncertainty about inflation. During crises periods, the strength of the transmission of inflation uncertainty shocks from one country to another tends to intensify. This paper examines empirical methodologies to measure the strength of the interdependence of inflation uncertainty between the UK and the euro area. We first estimate inflation uncertainty by expost forecast errors from a bivariate VAR GARCH model. The interdependence of uncertainty is estimated using a probability model. The results imply that the spillover of uncertainty is stronger for uncertainty about distant future than near future. The evidence from quantile regressions shows that such empirical method could suffer from bias if endogeneity is not properly addressed. To identify structural parameters in an endogeneity representation of interdependence, we exploit heteroskedasticity in the data across different regimes determined by the ratio of variances. The results no longer exhibit stronger interdependence at longer horizons. Estimated by different sample periods, the strength of the propagation of inflation uncertainty intensifies during the Global Financial Crisis while the interdependence significantly weakens during the post-crisis period

Three essays on uncertainty: real and financial effects of uncertainty shocks

The thesis consists of three essays on real and financial effects of uncertainty shocks. The first chapter investigates two different news-based uncertainty indices, Economic Policy Uncertainty Index (EPU) and Relative Sentiment Shift Index (RSS). I employ reduced form VAR and local projections (Jordá, 2005) to explore the differences in wait-and-see effect of uncertainty on the real economy. Surprises in either index lead to significant declines in production and employment and the effect is larger and persistent in the case of RSS shocks than EPU. In the second chapter, the probabilistic approach is applied to uncover the dependence structure in inflation uncertainty for the countries bordering a major currency area, the UK and the euro area. Inflation uncertainty is measured by the conditional volatility removing entire forecastable variations by bivariate VAR GARCH model and joint distribution of uncertainties of two regions is estimated by using copula to account for non-linear association. The results show that the left tail events of inflation are positively correlated between the two regions. This implies that the appropriate monetary policy can be drawn if policymakers consider the interconnectedness of the deflationary pressures. Finally, the third chapter examines the long run relationship between gross capital flow and its determinants, focusing on the impact of uncertainty as global and contagion factors. I apply bounds testing approach by Pesaran, Shin, and Smith (2001) allowing for he underlying regressors being either I(0), I(1) or mutually cointegrated. Both gross capital inflows and outflows exhibit significant level relationship with global, contagion and domestic factors and uncertainty spillovers through financial linkages between the UK and the euro area play crucial role in predicting capital flows of the UK

Alcohol Dependence in Mice: A Cocktail of Change in Region-specific mRNA Concentration and Protein Amount

Alcohol dependence poses great challenges against addressing Alcohol Use Disorders (AUD) by increasing tolerance to the drug’s adverse effects and inducing distressing withdrawal symptoms. With chronic alcohol use, the brain adjusts to recurrent excessive inhibitory signaling through physiological changes to upregulate excitatory neurotransmission. In particular, glutamate-detecting α-amino-3-hydroxy-5-methyl-4 isoxazolepropionic acid receptor (AMPAR) increases in synaptic density and activity upon prolonged alcohol use by an unknown mechanism. The shift towards glutamate signaling is indicative of neuroplasticity and anxiety-like symptoms that favor elevated alcohol drinking patterns. To identify the mechanism as to which dependence develops through the AMPAR pathway, C57BL/6J mice underwent the wellestablished Chronic Intermittent Ethanol (CIE) exposure to induce physiological responses similar to those observed in alcohol dependence in humans. Then, through qRT-PCR, gene expression of AMPAR pathway components associated with alcohol drinking behavior (GluA1,TARP-8, and PSD-95) were observed in brain regions (Prefrontal Cortex, Amygdala, Insular Cortex, and Nucleus Accumbens) particularly sensitive to excitatory signaling and interconnected in the reward pathway. Gene expression changes were then verified with relative protein concentrations to ensure processing of mRNA for activity. Significant changes indicate modulation of components of interest, which project onto the Nucleus Accumbens to retain neural homeostasis. In relation to protein concentration, further experimentation, such as varying decapitation time, is necessary to account for additional cellular and biochemical considerations such as mRNA and protein processing, time in between and during transcription and translation, and reaction with the inter- and intracellular environment. Follow up studies to this experiment will provide clearer insight into molecular targets for pharmacological AUD interventions.Bachelor of Art

Smart Information Exchange for Unsupervised Federated Learning via Reinforcement Learning

One of the main challenges of decentralized machine learning paradigms such as Federated Learning (FL) is the presence of local non-i.i.d. datasets. Device-to-device transfers (D2D) between distributed devices has been shown to be an effective tool for dealing with this problem and robust to stragglers. In an unsupervised case, however, it is not obvious how data exchanges should take place due to the absence of labels. In this paper, we propose an approach to create an optimal graph for data transfer using Reinforcement Learning. The goal is to form links that will provide the most benefit considering the environment's constraints and improve convergence speed in an unsupervised FL environment. Numerical analysis shows the advantages in terms of convergence speed and straggler resilience of the proposed method to different available FL schemes and benchmark datasets

The impact of geopolitical risk on stock returns: Evidence from inter-Korea geopolitics

We investigate how corporate stock returns respond to geopolitical risk in the case of South Korea, which has experienced large and unpredictable geopolitical swings that originate from North Korea. To do so, a monthly index of geopolitical risk from North Korea (the GPRNK index) is constructed using automated keyword searches in South Korean media. The GPRNK index, designed to capture both upside and downside risk, corroborates that geopolitical risk sharply increases with the occurrence of nuclear tests, missile launches, or military confrontations, and decreases significantly around the times of summit meetings or multilateral talks. Using firm-level data, we find that heightened geopolitical risk reduces stock returns, and that the reductions in stock returns are greater especially for large firms, firms with a higher share of domestic investors, and for firms with a higher ratio of fixed assets to total assets. These results suggest that international portfolio diversification and investment irreversibility are important channels through which geopolitical risk affects stock returns

Ginsenoside Rg3 Reduces Lipid Accumulation with AMP-Activated Protein Kinase (AMPK) Activation in HepG2 Cells

Cardiovascular disease (CVD) is one of the main causes of mortality worldwide, and dyslipidemia is a major risk factor for CVD. Ginseng has been widely used in the clinic to treat CVD. Ginsenoside Rg3, one of the major active components of ginseng, has been reported to exhibit antiobesity, antidiabetic, and cardioprotective effects. However, the effect of ginsenoside Rg3 on hepatic lipid metabolism remains unclear. Therefore, we investigated whether ginsenoside Rg3 would regulate hepatic lipid metabolism with AMP-activated protein kinase (AMPK) activation in HepG2 cells. Ginsenoside Rg3 significantly reduced hepatic cholesterol and triglyceride levels. Furthermore, ginsenoside Rg3 inhibited expression of sterol regulatory element binding protein-2 (SREBP-2) and 3-hydroxy-3-methyl glutaryl coenzyme A reductase (HMGCR). Ginsenoside Rg3 increased activity of AMPK, a major regulator of energy metabolism. These results suggest that ginsenoside Rg3 reduces hepatic lipid accumulation with inhibition of SREBP-2 and HMGCR expression and stimulation of AMPK activity in HepG2 cells. Therefore, ginsenoside Rg3 may be beneficial as a food ingredient to lower the risk of CVD by regulating dyslipidemia

Mapping mHealth (mobile health) and mobile penetrations in sub-Saharan Africa for strategic regional collaboration in mHealth scale-up: an application of exploratory spatial data analysis

AfDB: African Development Bank; CHMI: Center for Health Market Innovation; CIDA: Canadian International Development Agency; COMESA: Common Market for Eastern and Southern Africa; DFID: UK Department for International Development; ECCAS: Economic Community of Central African States; ECOWAS: Economic Community of West African States; ESDA: Exploratory Spatial Data Analysis; GADM: Global Administrative Areas; GIS: Geographic Information System; GNI: Gross National Income; ICT: Information Communication Technology; LISA: Local Indicator of Spatial Association; LMICs: Low- and Middle-Income Countries; mHealth: Mobile Health; MMS: Multimedia Message Service; NGOs: Non-governmental Organizations; PDA: Personal Digital Assistant; SIM: Subscriber Identity Module; SMS: Short Message Service; USAID: United States Agency for International Development; WHO: World Health OrganizationAbstract Background Mobile health (mHealth), a term used for healthcare delivery via mobile devices, has gained attention as an innovative technology for better access to healthcare and support for performance of health workers in the global health context. Despite large expansion of mHealth across sub-Saharan Africa, regional collaboration for scale-up has not made progress since last decade. Methods As a groundwork for strategic planning for regional collaboration, the study attempted to identify spatial patterns of mHealth implementation in sub-Saharan Africa using an exploratory spatial data analysis. In order to obtain comprehensive data on the total number of mHelath programs implemented between 2006 and 2016 in each of the 48 sub-Saharan Africa countries, we performed a systematic data collection from various sources, including: the WHO eHealth Database, the World Bank Projects & Operations Database, and the USAID mHealth Database. Additional spatial analysis was performed for mobile cellular subscriptions per 100 people to suggest strategic regional collaboration for improving mobile penetration rates along with the mHealth initiative. Global Morans I and Local Indicator of Spatial Association (LISA) were calculated for mHealth programs and mobile subscriptions per 100 population to investigate spatial autocorrelation, which indicates the presence of local clustering and spatial disparities. Results From our systematic data collection, the total number of mHealth programs implemented in sub-Saharan Africa between 2006 and 2016 was 487 (same programs implemented in multiple countries were counted separately). Of these, the eastern region with 17 countries and the western region with 16 countries had 287 and 145 mHealth programs, respectively. Despite low levels of global autocorrelation, LISA enabled us to detect meaningful local clusters. Overall, the eastern part of sub-Saharan Africa shows high-high association for mHealth programs. As for mobile subscription rates per 100 population, the northern area shows extensive low-low association. Conclusions This study aimed to shed some light on the potential for strategic regional collaboration for scale-up of mHealth and mobile penetration. Firstly, countries in the eastern area with much experience can take the lead role in pursuing regional collaboration for mHealth programs in sub-Saharan Africa. Secondly, collective effort in improving mobile penetration rates for the northern area is recommended