Search results for: household financial fragility

Authors: Sogand Barghi

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The integration of artificial intelligence (AI) in accounting practices is reshaping the landscape of financial management. This paper explores the innovative applications of AI in the realm of accounting, emphasizing its transformative impact on efficiency, accuracy, decision-making, and financial insights. By harnessing AI's capabilities in data analysis, pattern recognition, and automation, accounting professionals can redefine their roles, elevate strategic decision-making, and unlock unparalleled value for businesses. This paper delves into AI-driven solutions such as automated data entry, fraud detection, predictive analytics, and intelligent financial reporting, highlighting their potential to revolutionize the accounting profession. Artificial intelligence has swiftly emerged as a game-changer across industries, and accounting is no exception. This paper seeks to illuminate the profound ways in which AI is reshaping accounting practices, transcending conventional boundaries, and propelling the profession toward a new era of efficiency and insight-driven decision-making. One of the most impactful applications of AI in accounting is automation. Tasks that were once labor-intensive and time-consuming, such as data entry and reconciliation, can now be streamlined through AI-driven algorithms. This not only reduces the risk of errors but also allows accountants to allocate their valuable time to more strategic and analytical tasks. AI's ability to analyze vast amounts of data in real time enables it to detect irregularities and anomalies that might go unnoticed by traditional methods. Fraud detection algorithms can continuously monitor financial transactions, flagging any suspicious patterns and thereby bolstering financial security. AI-driven predictive analytics can forecast future financial trends based on historical data and market variables. This empowers organizations to make informed decisions, optimize resource allocation, and develop proactive strategies that enhance profitability and sustainability. Traditional financial reporting often involves extensive manual effort and data manipulation. With AI, reporting becomes more intelligent and intuitive. Automated report generation not only saves time but also ensures accuracy and consistency in financial statements. While the potential benefits of AI in accounting are undeniable, there are challenges to address. Data privacy and security concerns, the need for continuous learning to keep up with evolving AI technologies, and potential biases within algorithms demand careful attention. The convergence of AI and accounting marks a pivotal juncture in the evolution of financial management. By harnessing the capabilities of AI, accounting professionals can transcend routine tasks, becoming strategic advisors and data-driven decision-makers. The applications discussed in this paper underline the transformative power of AI, setting the stage for an accounting landscape that is smarter, more efficient, and more insightful than ever before. The future of accounting is here, and it's driven by artificial intelligence.

Keywords: artificial intelligence, accounting, automation, predictive analytics, financial reporting

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Authors: Disha Batra

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The Industrial Revolution 4.0 is quite different, and a paradigm shift is underway in the media industry. With the advent of automated journalism and social media platforms, newspaper organizations have changed the way news was gathered and reported. The emergence of the fourth industrial revolution in the early 21st century has made the newspapers to adapt the changing technologies to remain relevant. This paper investigates the content of Indian business-papers in the era of the fourth industrial revolution and how these organizations have emerged in the time of convergence. The study is the content analyses of the top three Indian business dailies as per IRS (Indian Readership Survey) 2017 over a decade. The parametric analysis of the different parameters (source of information, use of illustrations, advertisements, layout, and framing, etc.) have been done in order to come across with the distinct adaptations and modifications by these dailies. The paper significantly dwells upon the thematic analysis of these newspapers in order to explore and find out the coverage given to various sub-themes of EBF (economic, business, and financial) journalism. Further, this study reveals the effect of high-speed algorithm-based trading, the aftermath of the fourth industrial revolution on the creative and investigative aspect of delivering financial stories by these respective newspapers. The study indicates a change heading towards an ongoing paradigm shift in the business newspaper industry with an adequate change in the source of information gathering along with the subtle increase in the coverage of financial news stories over the time.

Keywords: business-papers, business news, financial news, industrial revolution 4.0.

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Authors: Pooja Rawat, Rakhi Tyagi

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Globally, almost 3 billion people rely on biomass (wood, charcoal, dung and crop residues) and coal as their primary source of domestic energy. Cooking and heating with solid fuels on open fire give rise to major pollutants. Women are primarily affected by these pollutants as they spend most of their time in the house. The WHO World Health Report 2002 estimates that indoor air pollution (IAP) is responsible for 2.7% of the loss of disability adjusted life years (DALYs) worldwide and 3.7% in high mortality developing countries. Indoor air pollution has the potential to not only impact health, but also impact the general economic well-being of the household. Exposure to high level of household pollution lead to acute and chronic respiratory conditions (e.g.: pneumonia, chronic obstructive pulmonary disease, lung cancer and cataract). There has been many strategies for reducing IAP like subsidize cleaner fuel technologies, for example use of kerosene rather than traditional biomass fuels. Another example is development, promotion of 'improved cooking stoves'. India, likely ranks second- distributing over 12 million improved stoves in the first seven years of a national program to develop. IAP should be reduced by understanding the welfare effects of reducing IAP within households and to understanding the most cost effective way to reduce it.

Keywords: open fire, indoor pollution, lung diseases, indoor air pollution

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Authors: Cristian Păuna

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After the widespread release of electronic trading, automated trading systems have become a significant part of the business intelligence system of any modern financial investment company. An important part of the trades is made completely automatically today by computers using mathematical algorithms. The trading decisions are taken almost instantly by logical models and the orders are sent by low-latency automatic systems. This paper will present a real-time price prediction methodology designed especially for algorithmic trading. Based on the price cyclicality function, the methodology revealed will generate price cyclicality bands to predict the optimal levels for the entries and exits. In order to automate the trading decisions, the cyclicality bands will generate automated trading signals. We have found that the model can be used with good results to predict the changes in market behavior. Using these predictions, the model can automatically adapt the trading signals in real-time to maximize the trading results. The paper will reveal the methodology to optimize and implement this model in automated trading systems. After tests, it is proved that this methodology can be applied with good efficiency in different timeframes. Real trading results will be also displayed and analyzed in order to qualify the methodology and to compare it with other models. As a conclusion, it was found that the price prediction model using the price cyclicality function is a reliable trading methodology for algorithmic trading in the financial market.

Keywords: algorithmic trading, automated trading systems, financial markets, high-frequency trading, price prediction

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Authors: Laura Rodríguez Amaya

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The impact of natural disasters on food security can be devastating, especially in rural settings where livelihoods are closely tied to their productive assets. In hazards studies, absorptive capacity is seen as a threshold that impacts the degree of people’s recovery after a natural disaster. Increasing our understanding of households’ capacity to absorb natural disaster shocks can provide the international community with viable measurements for assessing at-risk communities’ resilience to food insecurities. The purpose of this study is to identify the most important factors in determining a household’s capacity to absorb the impact of a natural disaster. This is an empirical study conducted in six communities in Costa Rica affected by earthquakes. The Earthquake Impact Index was developed for the selection of the communities in this study. The households coded as total loss in the selected communities constituted the sampling frame from which the sample population was drawn. Because of the study area geographically dispersion over a large surface, the stratified clustered sampling hybrid technique was selected. Of the 302 households identified as total loss in the six communities, a total of 126 households were surveyed, constituting 42 percent of the sampling frame. A list of indicators compiled based on theoretical and exploratory grounds for the absorptive capacity construct served to guide the survey development. These indicators were included in the following variables: (1) use of informal safety nets, (2) Coping Strategy, (3) Physical Connectivity, and (4) Infrastructure Damage. A multivariate data analysis was conducted using Statistical Package for Social Sciences (SPSS). The results show that informal safety nets such as family and friends assistance exerted the greatest influence on the ability of households to absorb the impact of earthquakes. In conclusion, communities that experienced the highest environmental impact and human loss got disconnected from the social networks needed to absorb the shock’s impact. This resulted in higher levels of household food insecurity.

Keywords: absorptive capacity, earthquake, food security, rural

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Authors: Kaila A. Vento

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Within the field of sports science, financial situations have been reported as a key barrier in purchasing high-quality foods. A lack of proper nutrition leads to insecurities of health, impairs training, and diminishes optimal performances. Consequently, insufficient nutrient intake, disordered eating patterns, and eating disorders may arise, leading to poor health and well-being. Athletic scholarships, nutrition resources, and meal programs are available, yet are disproportionally allocated, favoring male sports, Caucasian athletes, and higher sport levels. Direct athlete finances towards nutrition at various sport levels and the role race influences aid received has yet to be examined. Additionally, a diverse female athlete population is missing in the sports science literature, specifically in nutrition. To address this gap, the current project assesses how financial and nutrition support and nutrition knowledge impacts physical health, dietary intake, and overall quality of life of a diverse sample of female athletes at the National Collegiate Athletic Association (NCAA), National Junior Collegiate Athletic Association (NJCAA), and cub sport levels. The project will identify differences in financial support in relation to race, as well. Approximately (N = 120) female athletes will participate in a single 30-minute lab visit. At this visit, body composition (i.e., height, weight, body mass index, and fat percent), blood health indicators (fasted blood glucose and lipids), and resting blood pressure are measured. In addition, three validated questionnaires pertaining to nutrition knowledge (Sports Nutrition Knowledge Questionnaire; SNKQ), dietary intake (Rapid Eating Assessment for Participants; REAP), and quality of life (World Health Organization Quality of Life Brief; WHOQL-B) are gathered. Body composition and blood health indicators will be compared with the results of self-reported sports nutrition knowledge, dietary intake, and quality of life questionnaires. It is hypothesized that 1) financial and nutrition support and nutrition knowledge will differ between the sport levels and 2) financial and nutrition support and nutrition knowledge will have a positive association with quality of dietary intake and blood health indicators, 3) financial and nutrition support will differ significantly among racial background across the various competition levels, and 4) dietary intake will influence blood health indicators and quality of life. The findings from this study could have positive implications on athletic associations' policies on equity of financial and nutrition support to improve the health and safety of all female athletes across several sport levels.

Keywords: athlete, equity, finances, health, resources

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Authors: Chih-Mei Wang, Jon-Chao Hong, Jian-Hong Ye, Jing-Yun Fan, Chiao-Fei Lin

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The value of a certificate is to implement the criteria for evaluating work ability. Some professional certificates may make people feel good, but they are not useful in the workplace. To address this issue, this study is based on the expectancy-value model to take financial certificates as an example to explore how participants perceived the value of obtaining certification related to their usage perception of career promotion and salary increase. A total of 339 valid samples were subjected to confirmatory factor analysis and structural equation modeling; the results showed that the number of professional certificates was not significantly correlated with career promotion, but the number of professional certificates is negatively related to salary and benefits (S&B), while career promotion and S&B were positively related to job performance. The results show that the number of professional certificates does not play a significant role in the expectancy-value model. Therefore, professional certifications related to a basic level of finance was not expected to obtain in Taiwan's financial industry, and it is important to study the usefulness of some other certificates in other competitive industry.

Keywords: career promotion, certificate, compensation and benefits, goal-directed behaviors, Job performance

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Authors: Mojtaba Rezaei, Elham Heydari

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This paper highlights the empirical results of analyzing the correlation between accounting information and systematic risk. This association is analyzed among financial ratios and systematic risk by considering the financial statement of 39 companies listed on the Tehran Stock Exchange (TSE) for five years (2014-2018). Financial ratios have been categorized into four groups and to describe the special features, as representative of accounting information we selected: Return on Asset (ROA), Debt Ratio (Total Debt to Total Asset), Current Ratio (current assets to current debt), Asset Turnover (Net sales to Total assets), and Total Assets. The hypotheses were tested through simple and multiple linear regression and T-student test. The findings illustrate that there is no significant relationship between accounting information and market risk. This indicates that in the selected sample, historical accounting information does not fully reflect the price of stocks.

Keywords: accounting information, market risk, systematic risk, stock return, efficient market hypothesis, EMH, Tehran stock exchange, TSE

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Authors: Enas R. Shouman

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Economic development with population growth is leading to a continuous increase in energy demand. At the same time, growing global concern for the environment is driving to decrease the use of conventional energy sources and to increase the use of renewable energy sources. The objective of this study is to present the market trends of solar energy photovoltaic technology over the world and to represent economics methods for PV financial analyzes on the basis of expectations for the expansion of PV in many applications. In the course of this study, detailed information about the current PV market was gathered and analyzed to find factors influencing the penetration of PV energy. The paper methodology depended on five relevant economic financial analysis methods that are often used for investment decisions maker. These methods are payback analysis, net benefit analysis, saving-to-investment ratio, adjusted internal rate of return, and life-cycle cost. The results of this study may be considered as a marketing guide that helps diffusion of using PV Energy. The study showed that PV cost is economically reliable. The consumers will pay higher purchase prices for PV system installation but will get lower electricity bill.

Keywords: photovoltaic, financial methods, solar energy, economics, PV panel

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Authors: Neha Gupta, Sonika Verma, Seema Puri, Nikhil Tandon, Narendra K. Arora

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The concurrent increasing prevalence of underweight and overweight/obesity among children with changing lifestyle and the rapid transitioning society has necessitated the need for a unifying/multi-level approach to understand the determinants of the problem. The present community-based cross-sectional research study was conducted to assess the associations between lifestyle behavior and food environment of the child at household, neighborhood, and school with the BMI of children (6-12 year old) (n=612) residing in three rural clusters of Palwal district, Haryana. The study used innovative and robust methods for assessing the lifestyle and various components of food environment in the study. The three rural clusters selected for the study were located at three different locations according to their access to highways in the SOMAARTH surveillance site. These clusters were significantly different from each other in terms of their socio-demographic and socio-economic profile, living conditions, environmental hygiene, health seeking behavior and retail density. Despite of being different, the quality of living conditions and environmental hygiene was poor across three clusters. The children had higher intakes of dietary energy and sugars; one-fifth share of the energy being derived from unhealthy foods, engagement in high levels of physical activity and significantly different food environment at home, neighborhood and school level. However, despite having a high energy intake, 22.5% of the recruited children were thin/severe thin, and 3% were overweight/obese as per their BMI-for-age categories. The analysis was done using multi-variate logistic regression at three-tier hierarchy including individual, household and community level. The factors significantly explained the variability in governing the risk of getting thin/severe thin among children in rural area (p-value: 0.0001; Adjusted R2: 0.156) included age (>10years) (OR: 2.1; 95% CI: 1.0-4.4), the interaction between minority category and poor SES of the household (OR: 4.4; 95% CI: 1.6-12.1), availability of sweets (OR: 0.9; 95% CI: 0.8-0.99) and cereals (OR: 0.9; 95% CI: 0.8-1.0) in the household and poor street condition (proxy indicator of the hygiene and cleanliness in the neighborhood) (OR: 0.3; 95% CI: 0.1-1.1). The homogeneity of other factors at neighborhood and school level food environment diluted the heterogeneity in the lifestyles and home environment of the recruited children and their households. However, it is evident that when various individual factors interplay at multiple levels amplifies the risk of undernutrition in a rural community. Conclusion: These rural areas in Haryana are undergoing developmental, economic and societal transition. In correspondence, no improvements in the nutritional status of children have happened. Easy access to the unhealthy foods has become a paradox.

Keywords: transition, food environment, lifestyle, undernutrition, overnutrition

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Authors: Joachim Onyike

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The Federal Government of Nigeria in 2012 came up with a new National Housing Policy; one of its major objectives was to make housing affordable to the poor. Six years down the line, this study was carried out to find out whether the poor have fared better under the new housing policy. Owerri, the capital of Imo State, was adopted as a case study to mirror the situation nationwide. The study population was made up of low-income civil servants, i.e., grade levels 1–6 in the Imo State Civil Service. The study looked at household size, household income, rental levels, house prices, costs of major building materials, land values, land tenure, the interest rate on mortgages, inflation rate, and the status of government interventions, owing to their obvious effect on housing affordability by the low-income earners. The study made use of physical observations, questionnaires, and interviews as well as library studies to elicit relevant information. Housing affordability by the subject population did not improve. It rather dropped. The study came to the conclusion that in spite of the new National Housing Policy, housing affordability by the low-income earners has not improved. The policy as it affects the poor has not been duly implemented by both Federal and State Governments.

Keywords: house prices, housing affordability, housing policy, land values, low-income earners

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Authors: Wasfi Al Salamat, Shaker Al-Kharouf

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This study aims to examine the determinants of financial stability for 13 commercial banks listed on the Amman stock exchange (ASE) over the period (2007-2016) after controlling for the independent variables: return on equity (ROE), return on assets (ROA), earnings per share (EPS), growth in gross domestic product (GDP), inflation rate and debt ratio to measure the financial stability by three main variables: capital adequacy, non-performing loans and the number of returned checks. The balanced panel data statistical approach has been used for data analysis. Results are estimated by using multiple regression models. The empirical results suggested that there is statistically significant negative effect of inflation rate and debt ratio on the capital adequacy while there is statistically significant positive effect of growth in gross domestic product on capital adequacy. In contrast, there is statistically significant negative effect of return on equity and growth in gross domestic product on the non-performing loans while there is statistically significant positive effect of inflation rate on non-performing loans. Finally, there is statistically significant negative effect of growth in gross domestic product on the number of returned checks while there is statistically significant positive effect of inflation rate on the number of returned checks.

Keywords: capital adequacy, financial stability, non-performing loans, number of returned checks, ASE

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Authors: Kalandi Charan Pradhan

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In this study, we investigate does weather variation determine temporary labour migration using 210 sample households from six Semi-Arid Tropic (SAT) villages for the period of 2005-2014 in India. The study has made an attempt to examine how households use temporary labour migration as a coping mechanism to minimise the risk rather than maximize the utility of the households. The study employs panel Logit regression model to predict the probability of household having at least one temporary labour migrant. As per as econometrics result, it is found that along with demographic and socioeconomic factors; weather variation plays an important role to determine the decision of migration at household level. In order to capture the weather variation, the study uses mean crop yield deviation over the study periods. Based on the random effect logit regression result, the study found that there is a concave relationship between weather variation and decision of temporary labour migration. This argument supports the theory of New Economics of Labour Migration (NELM), which highlights the decision of labour migration not only maximise the households’ utility but it helps to minimise the risks.

Keywords: temporary migration, socioeconomic factors, weather variation, crop yield, logit estimation

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Authors: Rasikha Ramanand, Priyanka Dixit

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Background: Continuum of maternal care which includes antenatal care, delivery care and postnatal care aids in averting maternal deaths. The objective of this paper is to identify the association between previous experiences of child death on Continuum of Care (CoC) of recent child. Further, the study aimed at understanding where the drop-out rate was high in the continuum. Methods: The study was based on the Nation-wide District Level Household and Facility Survey (DLHS-4) conducted during 2012-13, which provides information on antenatal care, delivery care, percentage of women who received JSY benefits, percentage of women who had any pregnancy, delivery, the place of delivery etc. The sample included women who were selected from the non-EAG states who delivered at least two children. The data were analyzed using SPSS 20.Binary Logistic regression was applied to the data in which the Continuum of Care (CoC) was the dependent variable while the independent variables were entered as the covariates. Results: A major finding of the study was the antenatal to delivery care period where the drop-out rates were high. Also, it was found that a large proportion of women did not receive any of the services along the continuum. Conclusions: This study has clearly established the relationship between previous history of child loss and continuum of maternal care.

Keywords: antenatal care, continuum of care, child loss, delivery care, India, maternal health care, postnatal care

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Authors: Rudolph Carl Barrientos, Juwaln Diego Descallar, Rainer James Palmiano

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Household Appliance Scheduling Systems (HASS) coupled with a Time-of-Use (TOU) pricing scheme, a form of Demand Side Management (DSM), is not widely utilized in the Philippines’ residential electricity sector. This paper’s goal is to encourage distribution utilities (DUs) to adopt HASS and TOU by analyzing the effect of household schedulers on the electricity price and load profile in a residential environment. To establish this, a city based on an implemented survey is generated using Monte Carlo Analysis (MCA). Then, a Binary Particle Swarm Optimization (BPSO) algorithm-based HASS is developed considering user satisfaction, electricity budget, appliance prioritization, energy storage systems, solar power, and electric vehicles. The simulations were assessed under varying levels of user compliance. Results showed that the average electricity cost, peak demand, and peak-to-average ratio (PAR) of the city load profile were all reduced. Therefore, the deployment of the HASS and TOU pricing scheme is beneficial for both stakeholders.

Keywords: appliance scheduling, DSM, TOU, BPSO, city-wide simulation, electric vehicle, appliance prioritization, energy storage system, solar power

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Authors: Brian Basvi

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A technique for analyzing a security's intrinsic value is called fundamental analysis. It involves looking at relevant financial, economic, and other qualitative and quantitative aspects. Earnings Per Share (EPS), a crucial metric in fundamental analysis, is calculated by dividing a company's net income by the total number of outstanding shares. With more than 70 listed businesses, the Zimbabwe Stock Exchange (ZSE) is the primary stock exchange in Zimbabwe. This study applies the EPS financial ratio and stock valuation techniques to historical stock data from 68 companies listed on the Zimbabwe Stock Exchange. According to a ZSE study, EPS significantly affects share prices that are listed on the market. The study's objective was to assess how fundamental analysis affected the idea of EPS in ZSE stock valuation. It concluded that EPS is an important consideration for investors when they make judgments about their investments. According to the study's findings, fundamental analysis is a useful tool for ZSE investors since it offers insightful information about a company's financial performance and aids in decision-making. Investors can have a better understanding of a company's underlying worth and prospects for future growth by looking into EPS and other basic aspects.

Keywords: fundamental analysis, stock valuation, EPS, share pricing

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Authors: Wanda Luen-Wun Siu, Xiaowen Zhang

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This paper offered the primary methodical proof on how CSR reporting related to enterprise earnings in listed firms in China in light of most evidence focusing on cross-sectional data or data in a short span of time. Using full economic and business panel data on China’s publicly listed enterprise from 2006 to 2020 over two decades in the China Stock Market and Accounting Research database, we found initial evidence of significant direct relations between CSR reporting and firm corporate performance in both state-owned and privately owned firms over this period, supporting the stakeholder theory. Results also revealed that state-owned enterprises performed as well as private enterprises in the current period. But private enterprises performed better than state-owned enterprises in the subsequent years. Moreover, the release of social responsibility reports had a more significant impact on the financial performance of state-owned and private enterprises in the current period than in the subsequent periods. Specifically, CSR release was not significantly associated with the financial performance of state-owned enterprises on the lag of the first, second, and third periods. But it had an impact on the lag of the first, second, and third periods among private enterprises. Such findings suggested that CSR reporting helped improve the corporate financial performance of state-owned and private enterprises in the current period, but this kind of effect was more significant among private enterprises in the lag periods.

Keywords: China’s listed firms, CSR reporting, financial performance, panel analysis

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Authors: Sani AbdulRahman Bala

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This empirical study delves into the realm of forensic accounting practices within the Nigerian Public Sector, seeking to quantitatively analyze their efficacy in addressing the persistent challenges of fraud and financial irregularities. With a focus on empirical data, this research employs a robust methodology to assess the current state of fraud in the Nigerian Public Sector and evaluate the performance of existing forensic accounting measures. Through quantitative analyses, including statistical models and data-driven insights, the study aims to identify patterns, trends, and correlations associated with fraudulent activities. The research objectives include scrutinizing documented fraud cases, examining the effectiveness of established forensic accounting practices, and proposing data-driven strategies for enhancing fraud detection and prevention. Leveraging quantitative methodologies, the study seeks to measure the impact of technological advancements on forensic accounting accuracy and efficiency. Additionally, the research explores collaborative mechanisms among government agencies, regulatory bodies, and the private sector by quantifying the effects of information sharing on fraud prevention. The empirical findings from this study are expected to provide a nuanced understanding of the challenges and opportunities in combating fraud within the Nigerian Public Sector. The quantitative insights derived from real-world data will contribute to the refinement of forensic accounting strategies, ensuring their effectiveness in addressing the unique complexities of financial irregularities in the public sector. The study's outcomes aim to inform policymakers, practitioners, and stakeholders, fostering evidence-based decision-making and proactive measures for a more resilient and fraud-resistant financial governance system in Nigeria.

Keywords: fraud, financial irregularities, nigerian public sector, quantitative investigation

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Authors: Murad A. Bein

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This paper empirically examines the time-varying relationship and spillover effects between the international crude oil price and ten emerging equity markets, namely three oil-exporting countries (Brazil, Mexico, and Russia) and seven Central and Eastern European (CEE) countries (Bulgaria, Croatia, Czech Republic, Hungary, Poland, Romania, and Slovakia). The results revealed that there are spillover effects from oil markets into almost all emerging equity markets save Slovakia. Besides, the oil supply glut had a homogenous effect on the emerging markets, both net oil-exporting, and oil-importing countries (CEE). Further, the time variance drastically increased during financial turmoil. Indeed, the time variance remained high from 2009 to 2012 in response to aggregate demand shocks (global financial crisis and Eurozone debt crisis) and quantitative easing measures. Interestingly, the time variance was slightly higher for the oil-exporting countries than for some of the CEE countries. Decision-makers in emerging economies should therefore seek policy coordination when dealing with financial turmoil.

Keywords: crude oil, spillover effects, emerging equity, time-varying, aggregate demand shock

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Authors: Apedzan Emmanuel Kighir

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This research investigates dividends smoothing among non-financial companies trading on the Nigerian Stock Exchange in an era of unclaimed dividends from 2004 to 2013. There has been a raging controversy among Regulatory Authorities, Company Executives, Registrars of Companies, Shareholders and the general public regarding the increasing incidence of unclaimed dividends in Nigeria. The objective of this study is to find out if corporate earnings management through dividends smoothing is implicated in unclaimed dividends among Nigerian non-financial firms. The research used panel data and employed Generalized Method of Moment as method of analysis. The research finds evidence of dividends-smoothing in this era of unclaimed dividends in Nigeria. The research concludes that dividends-smoothing is a trigger and red flag for unclaimed dividends, an output of earnings management. If earnings management and hence unclaimed dividends in Nigeria is allowed to continue, it will lead to great consequences to the investors and corporate policy of government. It is believed that the research will assist investors and government in making informed decisions regarding dividends policy in Nigeria.

Keywords: dividends smoothing, non financial companies, Nigerian stock exchange, unclaimed dividends, corporate earnings management

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Authors: Joelle Thng, Li Fang

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Objective: As programming becomes a highly valued and sought-after skill in the economy, many universities have started offering Python courses to help students keep up with the demands of employers. This study focuses on designing a university module that effectively educates undergraduate students on financial analysis using Python programming. Methodology: To better satisfy the specific demands for each sector, this study adopted a qualitative research modus operandi to craft a module that would complement students’ existing financial skills. The lessons were structured using research-backed educational learning tools, and important Python concepts were prudently screened before being included in the syllabus. The course contents were streamlined based on criteria such as ease of learning and versatility. In particular, the skills taught were modelled in a way to ensure they were beneficial for financial data processing and analysis. Results: Through this study, a 6-week course containing the chosen topics and programming applications was carefully constructed for finance students. Conclusion: The findings in this paper will provide valuable insights as to how teaching programming could be customised for students hailing from various academic backgrounds.

Keywords: curriculum development, designing effective instruction, higher education strategy, python for finance students

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Authors: Khaldoon G. Albitar, Hassan Y. Kikhia, Jin P. Zhang

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Since 2007, all companies listed on both Shanghai Stock Exchange and Shenzhen Stock Exchange are required to prepare their consolidated financial statements in accordance with International Financial Reporting Standards (IFRS). This study investigates the impact of adopting IFRS on accounting quality for a sample of listed on Chinese companies during the period 2003-2013 with sample of 10846 observations over a four-year period before and a five-year period after the adoption of IFRS. This study tests whether the level of earnings management is significantly lower after the adoption of IFRS, and reported earnings is more value relevant during the IFRS period by using the Ohlson model and Jones model, as modified by Dechow. The empirical results show that accounting quality improved with lower earnings management and higher value relevant after the adoption of IFRS in China. The current study contributes to the literature on IFRS adoption and earning quality in two ways. First, As most of the existing studies on earnings quality and IFRS have been conducted on data from the U.S and European countries, this study fills a gap in the existing literature by studying the effect of adoption of IFRS on earnings quality in an emerging market. Second, the findings of our study have important implications for policymakers, auditors, multinational firms, and users of financial reports. As the rapid growth of China's economy gains global recognition, the Chinese stock market is capturing the attention of international investor.

Keywords: international financial reporting standards (ifrs), accounting quality, earnings management, value relevance, china

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Authors: Antonia Müller, Svend Reuse

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The Brexit referendum in June 2016 led to different publications analysing potential consequences for European and British insurance companies under the European Passport. This study addresses a research gap, regarding the measures taken by insurance companies based in the United Kingdom and thus on structural changes to the European insurance market by an innovative structured Solvency and Financial Condition Report content analysis. In scope are all insurance companies based in the United Kingdom, that fall under the Solvency II supervisory regime. The results show that the majority of British Solvency II insurance companies in scope, conducting cross-border business to the European Union, have applied and reported measures to be able to continue operating this cross-border business after Brexit. In addition, the study shows that 34 new insurance companies based in the European Union were established as a result of Brexit, indicating structural changes to the European insurance market.

Keywords: brexit, europe, insurance market, solvency and financial condition repot, structural changes

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Authors: Lubica Hikkerova, Jean-Michel Sahut

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Environmental protection remains a global challenge but, since 2012, there has been a progressive decline in corporate engagement in environmental protection issues. This study seeks to investigate the role of financial capacity and governance in improving the level of environmental engagement of companies. The regression technique is applied to data on 351 large European companies from the ASSET4-ESG database for the 2007-2015 period. Firstly, the results show that the companies in the sample are fairly engaged in environmental protection, with a strong dispersion representing nearly four times the average. This means that the companies in the sample do not share the same level of engagement in matters of environmental protection, some being more committed than others. Secondly, the results reveal that the financial capacity of the company, as assessed through its indicators, has a significant effect on its level of environmental protection engagement in the present sample. This effect is more positive the higher the profits the company makes, and more negative the more heavily indebted or, the higher the rates of dividends it pays per share. Lastly, the results also show that a better quality of governance plays an important role in the decision to undertake actions leading to environmental protection. More specifically, the degree of management implication in the running of the business, the respect of the rights of the shareholders, the effectiveness of the control exerted by the board of directors, and, to a lesser extent, the independence of the audit committee, are variables which have a positive and significant influence on the level of environmental engagement of companies.

Keywords: financial capacity, corporate governance, environmental engagement, stakeholder theory, theory of organizational legitimacy, theory of resources and capabilities

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Authors: Farid Khosravikia, Patricia Clayton

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The main objective of this work is to evaluate the advantages and disadvantages of various machine learning techniques in two key steps of seismic hazard and risk assessment of different types of structures. The first step is the development of ground-motion models, which are used for forecasting ground-motion intensity measures (IM) given source characteristics, source-to-site distance, and local site condition for future events. IMs such as peak ground acceleration and velocity (PGA and PGV, respectively) as well as 5% damped elastic pseudospectral accelerations at different periods (PSA), are indicators of the strength of shaking at the ground surface. Typically, linear regression-based models, with pre-defined equations and coefficients, are used in ground motion prediction. However, due to the restrictions of the linear regression methods, such models may not capture more complex nonlinear behaviors that exist in the data. Thus, this study comparatively investigates potential benefits from employing other machine learning techniques as statistical method in ground motion prediction such as Artificial Neural Network, Random Forest, and Support Vector Machine. The results indicate the algorithms satisfy some physically sound characteristics such as magnitude scaling distance dependency without requiring pre-defined equations or coefficients. Moreover, it is shown that, when sufficient data is available, all the alternative algorithms tend to provide more accurate estimates compared to the conventional linear regression-based method, and particularly, Random Forest outperforms the other algorithms. However, the conventional method is a better tool when limited data is available. Second, it is investigated how machine learning techniques could be beneficial for developing probabilistic seismic demand models (PSDMs), which provide the relationship between the structural demand responses (e.g., component deformations, accelerations, internal forces, etc.) and the ground motion IMs. In the risk framework, such models are used to develop fragility curves estimating exceeding probability of damage for pre-defined limit states, and therefore, control the reliability of the predictions in the risk assessment. In this study, machine learning algorithms like artificial neural network, random forest, and support vector machine are adopted and trained on the demand parameters to derive PSDMs for them. It is observed that such models can provide more accurate estimates of prediction in relatively shorter about of time compared to conventional methods. Moreover, they can be used for sensitivity analysis of fragility curves with respect to many modeling parameters without necessarily requiring more intense numerical response-history analysis.

Keywords: artificial neural network, machine learning, random forest, seismic risk analysis, seismic hazard analysis, support vector machine

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Authors: Pascal Horni, Sandro Fuchs

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In presence of increasing deficits and public debt among OECD countries, the debate on fiscal disciple and mechanisms to constrain public spending policy heated up and gave rise to the institutionalization of fiscal rules. Considering the notions from political economy literature and the therein advocated axiom of maximization of votes, introduction of institutional mechanisms and rules to govern public spending is likely to be coined by electoral motives. While there exists a series of research concerned with the rise of creative accounting in the presence fiscal rules, implementation of accrual government accounting and its impact on the biting of fiscal rules has to authors’ best knowledge never been explored. This paper serves the illumination of the connection between debt break mechanisms and the adoption of accrual public sector accounting standards such as the IPSAS in the interface of political economy in the Swiss context. By explicitly considering the technical accounting dimension, this paper develops an integrated conceptual view on well-established Public Financial Management (PFM) institutions and elaborates how their interdependencies can co-create value with regard to the contemporary challenge of fiscal sustainability. Derivation of this integrated view follows an explorative approach, taking into account expert interviews with director level staff from cantonal finance administrations and policy documents, as well as literature from both research areas – public sector accounting and political economy.

Keywords: accounting, fiscal rules, International Public Sector Accounting Standards (IPSAS), public financial management

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Authors: Nadezhda Kvatashidze, Elena Kharabadze

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It is broadly known that lease is a flexible means of funding enterprises. Lease reduces the risk related to access and possession of assets, as well as obtainment of funding. Therefore, it is important to refine lease accounting. The lease accounting regulations under the applicable standard (International Accounting Standards 17) make concealment of liabilities possible. As a result, the information users get inaccurate and incomprehensive information and have to resort to an additional assessment of the off-balance sheet lease liabilities. In order to address the problem, the International Financial Reporting Standards Board decided to change the approach to lease accounting. With the deficiencies of the applicable standard taken into account, the new standard (IFRS 16 ‘Leases’) aims at supplying appropriate and fair lease-related information to the users. Save certain exclusions; the lessee is obliged to recognize all the lease agreements in its financial report. The approach was determined by the fact that under the lease agreement, rights and obligations arise by way of assets and liabilities. Immediately upon conclusion of the lease agreement, the lessee takes an asset into its disposal and assumes the obligation to effect the lease-related payments in order to meet the recognition criteria defined by the Conceptual Framework for Financial Reporting. The payments are to be entered into the financial report. The new lease accounting standard secures supply of quality and comparable information to the financial information users. The International Accounting Standards Board and the US Financial Accounting Standards Board jointly developed IFRS 15: ‘Revenue from Contracts with Customers’. The standard allows the establishment of detailed revenue recognition practical criteria such as identification of the performance obligations in the contract, determination of the transaction price and its components, especially price variable considerations and other important components, as well as passage of control over the asset to the customer. IFRS 15: ‘Revenue from Contracts with Customers’ is very similar to the relevant US standards and includes requirements more specific and consistent than those of the standards in place. The new standard is going to change the recognition terms and techniques in the industries, such as construction, telecommunications (mobile and cable networks), licensing (media, science, franchising), real property, software etc.

Keywords: assessment of the lease assets and liabilities, contractual liability, division of contract, identification of contracts, contract price, lease identification, lease liabilities, off-balance sheet, transaction value

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Authors: Zasha Romero, Roberto Trevino, Lin Wang, Elizabeth Alanis, Jesus Cuellar

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Background: There is a strong relationship between low cardiorespiratory fitness (CRF) and high adiposity levels. The purpose of this study was to assess the effects of the Bienestar/Neema Coordinated School Health Program (BN CSHP) on the CRF of preschool children. Methods: This is a randomized cluster trial conducted in preschools of two school districts located along the Texas-Mexico border. Of 48 eligible schools, 28 were randomly selected (intervention, n=14; control, n=14). Family demographics and household health characteristics were collected from parents. CRF, as measured by the Progressive Anaerobic Capacity Endurance Run (PACER) fitness test, was collected from the children. A generalized linear mixed model (GLMM) was used to analyze the data. Results: Family demographics, household health characteristics, and children’s weight, obesity prevalence, and sedentary activity were similar among both treatment groups. After adjusting for covariates, the number of laps run by children in the control group increased by 23% (CI: -5% to 60%) per each data collection period compared with 53% (CI: 7% to 119%) in the intervention group. Conclusions: Children in the BN CSHP, compared to those in the control group, had a significantly higher increase in their CRF. This finding is important because of the health benefits of CRF in children.

Keywords: coordinated school health program, cardiorespiratory fitness, obesity, border health, preschool, physical education, movement

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Authors: Rizwan Fazal

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This study investigates the behavior of external sector of Pakistan economy and its impact on economic growth, using quarterly data for the period 1990:01-2010:04. External sector indices used in this study are financial integration, net foreign assets and trade integration. Augmented Ducky fuller confirms that all variables of external sector are non-stationary at level, but at first difference it becomes stationary. The co-integration test suggests one co-integrating variables in the study. The analysis is based on Vector Auto Regression model followed by Vector Error Correction Model. The empirical findings show that financial integration play important role in increasing economic growth in Pakistan economy while trade integration has negative effect on economic growth of Pakistan in the long run. However, the short run confirms that output lag accounts for error correction. The estimated CUSUM and CUSUMQ stability test provide information that the period of the study equation remains stable.

Keywords: financial integration, trade integration, net foreign assets, gross domestic product

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Authors: A. Majeed, P. Ali

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Before designing an electrical system, the estimation of load is necessary for unit sizing and demand-generation balancing. The system could be a stand-alone system for a village or grid connected or integrated renewable energy to grid connection, especially as there are non–electrified villages in developing countries. In the classical model, the energy demand was found by estimating the household appliances multiplied with the amount of their rating and the duration of their operation, but in this paper, information exists for electrified villages could be used to predict the demand, as villages almost have the same life style. This paper describes a method used to predict the average energy consumed in each two months for every consumer living in a village by Artificial Neural Network (ANN). The input data are collected using a regional survey for samples of consumers representing typical types of different living, household appliances and energy consumption by a list of information, and the output data are collected from administration office of Piramagrun for each corresponding consumer. The result of this study shows that the average demand for different consumers from four villages in different months throughout the year is approximately 12 kWh/day, this model estimates the average demand/day for every consumer with a mean absolute percent error of 11.8%, and MathWorks software package MATLAB version 7.6.0 that contains and facilitate Neural Network Toolbox was used.

Keywords: artificial neural network, load estimation, regional survey, rural electrification

Procedia PDF Downloads 119