Miracle-dz/UniFAR-FTUs huggingface dataset:
Hybrid Bonds as a strategy of sequential finance in the banking sector

Up to this point, the literature on the issuance of convertible bonds has neglected financial institutions. Contrary to firms, banks not only can issue convertible bonds but also, after the subprime crises, contingent convertible (CoCo) bonds emerged as an alternative. Hence, the purpose of this study is threefold: first, we expand the literature on the motivation to issue convertible bonds in the banking sector; second, we introduce a new proxy (Loans-Deposits Flow) to measure the reinvestment in this sector; and third, we analyze the differences in the motivation for issuing CoCo bonds when compared to convertible bonds. Our results show that the theory of sequential financing is not confirmed for CoCo bonds in the banking sector. Additionally, we provide evidence that banks issue CoCo bonds for regulatory purposes (to increase their capital), while convertibles are issued to allow banks to expand their investments and loan portfolios. The results are robust to several specifications including a propensity-score matching and a difference-in-difference analysis.
Disaggregated Government Expenditure and Economic Development in Nigeria: An Econometric Analysis.

This study empirically examined disaggregated government expenditure and economic development in Nigeria using data spanning between the periods 1981 to 2020 by employing the use of Augmented Dickey Fuller test, Co integration test and Vector Error Correction technique (VECM) as the statistical techniques of analysis. From the study, the error correction model is -0.709 and it shows that about 70.9 percent of the short run shocks in Human Capital Development (HDI) in Nigeria are adjusted annually and such high speed of adjustment is very fundamental in the process of policy conception, formulation and implementation. This aforementioned finding revealed that there is a long run equilibrium relationship between human development index and various government expenditures variables as shown by the error correction model which is very high, rightly signed and significant. Also, the results show that in the long run that government expenditure on social security, government expenditure on education, health expenditure and agricultural expenditure have a positive and significant impact on human development index while government expenditure on infrastructure has a negative but significant effect on human development index in Nigeria. Furthermore, the short run estimates show that government expenditure on infrastructure (GEI) has a significant effect on HDI at lag period one and two while government expenditure on education and government expenditure on agriculture were found to be significant at lag period one respectively. Conversely, government expenditure on social security and government expenditure on health have a direct and insignificant effect on human development index in Nigeria. By implication, the findings indicate that government spending play a crucial role in the development of human capital in Nigeria. The study therefore concludes that there is need for federal government to be consistent in allocation and redistribution of government spending to various key sectors of the economy such as education, health, agriculture and defence which will invariably contribute positively and significantly to the human development in the country. Finally, there is need to ensure that federal government appropriate more funds to these key sectors annually.
Structural Transformation, Agriculture, Climate, and the Environment

This paper reviews the feedback between structural transformation and agriculture, on the one hand, and climate and the natural environment, on the other. The long-standing, dominant economic development narrative largely ignores nature’s influence on factor productivity and stocks, even as it increasingly illustrates how agricultural technological change and economic growth affect nature. We articulate some of the missing linkages and pose key policy research questions concerning structural transformation and the complex feedback among agriculture, nature, and economic growth processes, especially in low-income agrarian economies.
The Impact of Financial Inclusion on the Economic Empowerment of Nigerian Women

This study provides a review of financial inclusion and women empowerment in Nigeria using secondary data. This research has highlighted the state of financial inclusion in Nigeria for women and compared same to other countries in the world. Firstly, it identifies the Conflict Theory and the Integrated Ecological Framework as concepts that give credence to my research and position on the discrimination of women, considering the context of the society in question. It has identified the global, regional, and local frameworks for financial inclusion and women’s rights as adopted by Nigeria. Secondly, it draws particular attention to the barriers of financial inclusion, and it identifies the traditional indicators for financial inclusion globally, and uses these benchmarks to independently ascertain if there indeed exists a relationship between access to these financial inclusion indexes and the economic empowerment of a Nigerian woman. Thirdly, this research draws attention to the financial inclusion policy and implementation activities of other countries as well as the discovery of the Income Level Paradox, which appears to be a trap that a lot of women have found themselves in; especially in the North of the country. In addition, Northern Nigeria has been identified as the major influence in the gap that Nigeria has experienced in meeting its financial inclusion target, and it has been highlighted as a limitation and a potential area for research in future studies, likewise the Income Level Paradox and household income control for women. Deductively, our key findings have it that Nigerian women are financially excluded and there are barriers, which when resolved can foster financial inclusion, and potentially economic empowerment for these women. Recommendations have been made for bridging the financial inclusion gender gap (FIGG) for the North of Nigeria and the South as well. Finally, the issues deliberated on in this paper reveals limitations to this study which are avenues for further research in the area of breaking the 'Income Level Trap’ and resolving the FIGG in Northern Nigeria.
Polymer-based nanocomposites for heavy metal ions removal from aqueous solution: a review

Water pollutant treatment has become a critical issue in environmental engineering and protection. Adsorption techniques via solid adsorbents have been widely applied for the efficient removal of metal ions from wastewater solutions, where polymer-based composites have attracted much attention due to their intrinsic environmentally harmless and degradable properties. Particularly, polymer-based nanocomposites often present superior physical, chemical and mechanical properties, as well as superior compatibility, as compared with single polymers, by incorporating the advantages of both counterparts in the composites. This article is an overview of the versatile polymer-based composites containing different functional organic and/or inorganic counterparts for the removal of hazardous metal ions from wastewater. The synthesis of the adsorbents, adsorption process features and mechanism investigation are highlighted and discussed in detail. The future perspectives and trends in this field are also outlined. We hope that this review will provide some inspiring information for designing and fabricating polymer-based nanocomposites for the removal of diverse heavy metal ions from aqueous solution, and pollution management in the near future.
Risk-Taking and Tail Events Across Trading Institutions

We study the reaction of investors to tail events across trading institutions. We conduct experiments in which investors bid on a financial asset that delivers a small positive reward in more than 99% of the cases and a large loss otherwise. The baseline treatment uses a repeated BDM mechanism whereas the market treatment replaces the uniform draw of the BDM mechanism by a uniform draw over the bids of the other participants. Our design is such that bids should not differ across treatments in normal times while allowing for potential differences to emerge after tail events have occurred. We find that markets tend to exacerbate the reaction of investors to tail losses and we attribute this effect to emotions.
The Impact of Geopolitical Risk on Stock Returns: Evidence from Inter-Korea Geopolitics

English Abstract: 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.
Does uncertainty matter for trade flows of emerging economies?

Uncertainty shocks have been shown to affect the real economy, but uncertainty remains about their trade effects and whether effects are similar across different types of uncertainty. We investigate how global economic, financial, and trade policy uncertainty affect the trade flows of the seven largest emerging economies (EM-7) using a panel structural vector autoregressive model. We find that: (1) Global economic and trade policy uncertainty shocks induce a protracted decline of about 4 to 5% in EM-7’s imports and exports. (2) Global economic and trade policy uncertainty act as trade barriers, reducing the EM-7’s degree of openness and their trade balance to GDP ratio. (3) Financial uncertainty only has a short-term impact on EM-7’s trade flows. (4) Trade policy uncertainty is the most important type of uncertainty affecting trade flows, explaining 11% of the variation in trade flows.
Estimating Security Betas via Machine Learning

This paper evaluates the predictive performance of machine learning techniques in estimating time-varying betas of US stocks. Compared to established estimators, tree-based models and neural networks outperform from both a statistical and an economic perspective. Random forests perform the best overall. Machine learning-based estimators provide the lowest fore-cast errors. Moreover, unlike traditional approaches, they lead to truly ex-post market-neutral portfolios. The inherent model complexity is strongly time-varying. The most important predictors are various historical betas as well as fundamental turnover and size signals. Compared to linear regressions, interactions and nonlinear effects enhance the predictive performance substantially.
Why Does Risk Matter More in Recessions than in Expansions?

This paper uses a nonlinear vector autoregression and a non-recursive identification strategy to show that an equal-sized uncertainty shock generates a larger contraction in real activity when growth is low (as in recessions) than when growth is high (as in expansions). An estimated New Keynesian model with recursive preferences and approximated to third order around its risky steady state replicates these state-dependent responses. The key mechanism behind this result is that firms display a stronger upward nominal pricing bias in recessions than in expansions, because recessions imply higher inflation volatility and higher marginal utility of consumption than expansions.
Does board gender diversity weaken or strengthen executive risk-taking incentives?

We investigate the effect of board gender diversity on managerial risk-taking incentives. Our results demonstrate that companies with stronger board gender diversity provide more powerful executive risk-taking incentives. It appears that female directors’ risk aversion exacerbates managers’ risk aversion, resulting in a sub-optimal level of risk-taking. To offset this tendency for too little risk, companies are induced to provide stronger risk-taking incentives. Specifically, an increase in board gender diversity by one standard deviation raises vega by 10.3%. Further analysis corroborates the results, including propensity score matching, entropy balancing, and an instrumental-variable analysis. Endogeneity appears to be unlikely, suggesting that female directors are not merely associated with, but probably bring about stronger risk-taking incentives.
Cellular and Cytokine Responses in Lymph Node Granulomas of Bacillus Calmette Guérin (BCG)-Vaccinated and Non-vaccinated Cross-Breed Calves Naturally Infected With Mycobacterium bovis

Local immunological responses at the site of infections, such as at the lymph nodes and lungs, do play a role in containing infection caused by Mycobacterium bovis (M. bovis). This bovine tuberculosis (bTB) study was conducted to evaluate cellular and cytokine responses in the lymph nodes and lungs of BCG-vaccinated and non-vaccinated calves that were naturally infected with M. bovis. Immunohistochemical assays were used for examination of the responses of macrophages, T cells, cytokines and chemical mediators of 40 (22 vaccinated and 18 non-vaccinated) Holstein-Friesian-zebu crossbred calves that were naturally exposed for 1 year to a known bTB positive cattle herd. The incidence rates of bTB visible lesion were 68.2% (15/22) and 89% (16/18) in vaccinated and non-vaccinated calves, respectively. The local responses of CD4+ and CD8+ T cells, and those of IFN-γ and TNF-α within the lesions, were stronger (P < 0.05) in BCG-vaccinated calves than in non-vaccinated calves. However, there was no statistically significant difference between the two groups (P > 0.05) in the response of CD68+ cells. Thus, the findings of this study indicated stronger responses of a set of immunological cells and markers at the local granulomas of BCG-vaccinated calves than in non-vaccinated calves. Furthermore, BCG vaccination may also play a role in reducing the severity of the gross pathology at the primary site of infection.
Effects of enhanced hydrogen bonding on the mechanical properties of poly (vinyl alcohol)/carbon nanotubes nanocomposites

Abstract In this study, poly (vinyl alcohol) (PVA) composites reinforced by multiwall carbon nanotubes (MWCNTs) functionalized with either phenolic hydroxyl groups (MWCNTs-f-OH) or PVP molecule (PVP@MWCNTs) were fabricated. The objective was to elucidate the effect of different MWCNTs surface functionalization on the mechanical properties of the nanocomposites. It was found that both of PVP@MWCNTs and MWCNTs-f-OH had a good dispersion in PVA matrix. However, the MWCNTs-f-OH had stronger effective interfacial interaction with PVA matrix than PVP@MWCNTs, owe to the formation of hydrogen bonds between MWCNTs-f-OH and PVA. The stress-strain measurements showed that the Young’s modulus and tensile strength of MWCNTs-f-OH/PVA with only 1.0 wt. % contents increased by 200 and 100% compare with that of PVA, respectively. The findings of this experimental study emphasized the critical role of MWCNTs surface morphology in determining the mechanical properties of nanocomposites, and shed new light on understanding and advancing the properties of carbon nanotube based composites.
Catha edulis Forsk and Ascorbic Acid Effects on Hematological Indices in Rat

Background The prevalence of chewing Catha edulis Forsk and the use of ascorbic acid is increasing from time to time. Their subchronic effects on hematological indices are not well examined. The present study was aimed to investigate their subchronic effects on hematological indices in rats. Materials and Methods A total of 36 adult (7–8 weeks) wild-type rats weighing between 213 and 229g were used in this study. They received Catha edulis Forsk extract (Ce) (100 milligrams/kilogram, 200 milligram/kilogram and 300 milligram/kilogram b.w), Catha edulis Forsk juice (2.5 mL/kg), ascorbic acid (AA 200 milligram/kilogram), and 2% tween 80 in distilled water (T80W- v/v) for twelve weeks. Hematological indices were measured with Sysmex KX-21. Data were analyzed by SPSS version 21.0 and Microsoft Excel. Results Neutrocytes (p < 0.01), lymphocytes (p < 0.05), plateletcrit (p < 0.05), average size of platelets (p < 0.05), platelet size variability (p < 0.01), platelet–large cell ratio (p < 0.05) and neutrocytes/lymphocytes ratio (p < 0.001) were significantly greater, while hemoglobin concentration per red blood cell (p < 0.05) and hemoglobin concentration per volume of red blood cells were significantly reduced (p < 0.05) in rats received khat. The red cell distribution width (p < 0.05), platelet size variability (p < 0.05) and platelet–large cell ratio (p < 0.01) were significantly greater in rats received ascorbic acid. Conclusion Crude Catha edulis Forsk extract and juice changed some hematological indices and increased platelet activities. The platelet activity was also increased by ascorbic acid. The mechanisms for these changes need to be investigated.
The Relationship Between COVID-19 Infection Rates and Social Determinants of Health in Broward and Miami-Dade Counties, Florida

Objective To determine the relationship between per capita income and COVID-19 cases in Broward and Miami-Dade Counties of Florida, USA. Background Low socioeconomic status predisposes individuals to worse health outcomes. For example, during the 2003 SARS-CoV pandemic and the 2009 H1N1 influenza pandemic disadvantaged individuals were more likely to become infected. More recently, a study found that deaths due to COVID-19 were associated with disadvantaged areas across the United States. South Florida, in particular Broward and Miami-Dade Counties, has experienced a significant burden of coronavirus cases. Investigating the association of income on coronavirus cases in Broward and Miami-Dade Counties may aid in identifying and treating those individuals at increased risk. Methods This retrospective cross-sectional study used data gathered by the Florida Department of Health and 2018 U.S. Census. COVID-19 cases from March 2 - November 1, 2020 were tallied by ZIP code in Florida’s Broward and Miami-Dade Counties and scaled per housing unit. An exhaustive regression analysis using County “Miami-Dade” or “Broward,” sex, race, ethnicity, median age, and estimated per capita income was performed for each combination of independent variables in MATLAB (MathWorks, Natick, USA). Regression models were evaluated using both adjusted R-squared and the Akaike Information Criterion, along with the number of significant predictors. The most optimal model with the highest number of significant predictors was selected. Results Among all other variables, sex, race, and ethnicity as the variables that best predicted COVID-19 cases per housing unit within a certain ZIP code. The adjusted R-squared of this optimal model was 0.5062, indicating that within each ZIP code in Broward and Miami-Dade Counties 50.62% of the variance in COVID-19 cases per housing unit can be explained by these variables. A significant relationship was found between the number of COVID-19 cases and individuals who were Black or African American (p < 0.001), individuals who were Hispanic or Latino (p < 0.001), and male to female ratio (p = 0.016). Per capita income, age, and county were not statistically significant predictors in any model tested. Conclusions Racial and gender disparities may be more significant contributors to COVID-19 cases than per capita income in housing units. Based on the results of this study, investigators may consider applying this model to similar variables in order to inform the management and prevention of cases in the present and future pandemics.
Integrated model for predicting rice yield with climate change

Abstract Rice is the chief agricultural product and one of the primary food source. For this reason, it is of pivotal importance for worldwide economy and development. Therefore, in a decision-support-system both for the farmers and in the planning and management of the country’s economy, forecasting yield is vital. However, crop yield, which is a dependent of the soil-bio-atmospheric system, is difficult to represent in statistical language. This paper describes a novel approach for predicting rice yield using artificial neural network, spatial interpolation, remote sensing and GIS methods. Herein, the variation in the yield is attributed to climatic parameters and crop health, and the normalized difference vegetation index from MODIS is used as an indicator of plant health and growth. Due importance was given to scaling up the input parameters using spatial interpolation and GIS and minimising the sources of error in every step of the modelling. The low percentage error (2.91) and high correlation (0.76) signifies the robust performance of the proposed model. This simple but effective approach is then used to estimate the influence of climate change on South Korean rice production. As proposed in the RCP8.5 scenario, an upswing in temperature may increase the rice yield throughout South Korea.
Efforts to Recruit Medical Students From Rural Counties: A Model to Evaluate Recruitment Efforts

Background Over the past 40 years, the physician supply of North Carolina (NC) grew faster than the total population. However, the distribution of physicians between urban and rural areas increased, with many more physicians in urban areas. In rural counties, access to care and health disparities remain concerning. As a result, the medical school implemented pipeline programs to recruit more rural students. This study investigates the results of these recruitment efforts. Methodology Descriptive analyses were conducted to compare the number and percentage of rural and urban students from NC who applied, interviewed, and were accepted to the University of North Carolina’s School of Medicine (UNC SOM). The likely pool of rural applicants was based on the number of college-educated 18-34-year-olds by county. Results Roughly 10.9% of NC’s population of college-educated 18-34-year-olds live in rural counties. Between 2017 and 2019, 9.3% (n = 225) of UNC SOM applicants were from a rural county. An increase of just 14 additional rural applicants annually would bring the proportion of rural UNC SOM applicants in alignment with the potential applicant pool in rural NC counties. Conclusions Our model of analysis successfully calculated the impact of recruitment efforts to achieve proportional parity in the medical school class with the rural population of the state. Addressing rural physician workforce needs will require multiple strategies that affect different parts of the medical education and healthcare systems, including boosting college completion rates in rural areas. This model of analysis can also be applied to other pipeline programs to document the success of the recruitment efforts.