Semi-annual Data Research Articles

Effects of credit rating changes on corporate capital structure in South Africa

Orientation: The changes in credit ratings for corporates have a great impact on corporate funding decisions, costs and capital structures.Research purpose: The study aimed to identify the relationship between credit ratings and capital structures in emerging economies such as South Africa.Motivation for study: Investors, financial managers, regulatory authorities and financial analysts focus on the credit quality of companies as measured by credit ratings in making financing and investing choices. The credit rating is a significant communication tool, and businesses consider it crucial when deciding on capital structure. An ideal capital structure of a company is one that reduces its relative cost of capital by striking a balance between the capital structure proportions to enhance value.Research approach, design and method: A systematic and quantitative approach using semi-annual data from 2011 to 2020 sourced from EquityRT and the JSE.Main findings: Credit ratings have a positive and material impact on the capital structure decisions of South Africa’s top 40 companies. Thus, a higher debt-to-asset ratio is encouraged when the credit score improves, and a downgrade is more likely to be followed by a capital reduction behaviour.Practical/managerial implications: Investors, managers and regulators can use the findings of this study for financial decision-making purposes, anticipating changes in future corporate capital structures and monitoring funding opportunities as well as balancing debt to equity in the capital construction of an organisation.Contribution/value-add: The evidence generated by the study presented that credit rating changes influence capital structure.

Islamic Banking and Unemployment: Determining Factors of Unemployment Rate and its Implications on Poverty Level

Purpose: This research aims to analyze whether the development of sharia banking and several other variables such as Gross Domestic Product (GDP), population and social factors have a significant effect on the unemployment rate and poverty alleviation in Indonesia. Method: this research uses quantitative research with the research object being Indonesian macroeconomic data using semiannual data for the period 2010 – 2020. The analysis used is multivariate analysis based on the Partial Least Square-Structural Equation Model (PLS-SEM). Results and conclusions: This research finds that social variables have a negative influence on the unemployment rate compared to population, Islamic banking, or GDP. Another finding is that GDP and Islamic banking have a very detrimental impact on poverty levels. This is different from the unemployment rate which has a positive impact. Regarding the use of mediating factors, namely the unemployment rate, it turns out that sharia banking, population and GDP do not have a significant effect on the poverty rate. However, the amount of poverty is negatively influenced by social variables. implications: This research provides implications for government policy to continue to strengthen capital policies, networks, education and socialization of sharia banking. Apart from that, systematic, conducive, serious and measurable positive efforts in various economic sectors will have an impact on poverty alleviation. Originality/value: This research offers novelty in the form of connecting Islamic banking with poverty levels and is found to have a negative relationship. We use data from 2010 to 2020. We suspect that this condition is caused by a lack of Indonesian government policies regarding capital, networks and education.

Financial Decisions and Value-at-Risk: Empirical Evidence from BIST 100 Companies

This study examines the relationship between financial decisions and the value-at-risk (VaR) of companies operating in the Turkish stock market. The study contains semi-annual data of non-financial BIST 100 Index companies spanning from January 2010 to June 2023. Companies’ VaR are calculated using Monte-Carlo simulation, bootstrap, delta-normal, and historical simulation methods and included in separate econometric models as dependent variables. Financial decisions are represented through financial ratios in line with the basic principles of corporate finance and included as explanatory variables in econometric models. The study employs a five-stage panel data methodology. 
 Findings reveal that the impact of financial decisions regarding working capital management, capital structure, dividend pay-out, and growth policies on companies’ VaR differ according to the VaR calculation method. Notably, findings show that financial decisions explain the changes in VaR calculated by Bootstrap method with the highest success rate, aligning with existing finance literature. Prudent financing policies and flexible investment strategies in working capital management, enhanced profitability and financial performance, and sales growth exhibit dampening effects on VaR. Conversely, heightened leverage and long-term borrowings, decisions to pay-out dividends, and growth in foreign investments have increasing effects on VaR. Furthermore, the study identifies the Covid-19 pandemic as exerting a negative influence on VaR.

Maize Production Forecasting in Iraq: A Box-Jenkins Approach for the Period of 2022-2026

This study aims to forecast the production of Iraq’s maize crop using Auto Regressive Integrated Moving Average (ARIMA) models. Using the semi-annual data for the period 1980-2021, the production of the maize crop was forecasted for 5 years, starting from 2022 to 2026. The data were obtained from the Ministry of Planning and International Cooperation, Planning and Monitoring Department, Agricultural Statistics Department, Iraq. The forecasted production of maize in Iraq during the period 2021-2026 is characterized by fluctuations between highs and lows, similar to the production of maize during the study period. The highest expected production value of maize in Iraq was in the second half of 2023, reaching 585 thousand tons, while the lowest expected production was 500 thousand tons in the first half of 2022. This study is significant in providing valuable insights that can guide the formulation of effective policies regarding maize production, pricing, and consumption in the country.

Tax Revenue and Economic Development in Nigeria

The study used ARDL model to examine tax revenue and economic development in Nigeria from 1999-2020. Thus, the objective is to determine the impact of indirect tax revenue (import duty and export duty) on economic development in Nigeria. This study employed ex-post- facto research design and used semi-annual data collected from Central Bank of Nigeria (CBN) statistical bulletin. The study adopted the econometric analysis of unit root test and the technique of auto regressive distributed lag (ARDL) model. Based on the empirical results, exports tax revenue positively impacted on economic development, while imports tax revenue has negative and insignificant relationship with economic development in Nigeria during the period of study. The implications of the finding is that the Nigerian government can boost economic growth and development by realizing the need to focus on boosting tax revenue from indirect tax sources while expanding the catchment of those liable to pay indirect taxes. Based on the findings of it was recommended that, government should formulate and implement export policy measures towards exporting goods that are growth and development drivers, particularly, refined goods in the area the nation has comparative advantage in order to make the domestic production viable and compete with the industrialized economy of the world. Also, government should identify administrative loopholes that drain the revenue from custom duties so that import tax revenue will contribute significantly to economic development.

The Impact of Political Instability, Food Prices, and Crime Rate on Tourism: A Way toward Sustainable Tourism in Pakistan

This study aims to examine the impact of political instability, food prices, and the crime rate on tourism development in Pakistan over the semi-annual data from 1995 to 2019. To achieve the goal of this study, an asymmetric ARDL technique was used. The Asymmetric Autoregressive Distributed Lag Model (ARDL) aided in gaining access to both positive and negative shocks in political stability, crime rate, and food inflation. The findings showed that due to positive variations in the political conditions, tourism will increase by 0.12%, and if political instability prevails in the country, tourism will decrease by 23%. On the other hand, the magnitude of political stability is less than the negative variation of political instability on tourism. The study concludes that there is a considerable asymmetric association between political instability, crime rate, food prices, and tourism development in Pakistan. Based on these findings, it is advised that the government adopt proactive measures to establish and reinforce the political stability mechanism and terrorism control, as well as to improve the living standards of the general population. Moreover, establish a structure for adaptation efforts, focusing on the coordination of tourism expansion platforms for sustainable tourism in Pakistan to attract more foreigners for the sake of a surge in tourism proceeds.

IFRS Adoption and the Financial Statements Comparability: The Case of Russia and Canada

The effect of International Financial Reporting Standards (IFRS) adoption on the level of financial statements comparability was investigated for Russia in the current article. Canada was chosen for comparison due to the close time frame of IFRS adoption, which also allowed comparing the influence of IFRS adoption for both types of economies – well developed and emerging. Initial sample selection had been created from 23 companies that are presented on the stock exchange markets of the particular countries. Each sample contains semi-annual data for four years of the pre-adoption period (2008 to 2011 for Russia, 2007 to 2010 for Canada) in which companies use their home country accounting standards and four years of the post-adoption period (2012 to 2015 for Russia, 2011 to 2014 for Canada) in which companies use IFRS standards. The research was performed on the country level and industry level for both countries. Two measures had been used for the research: earnings-return regression and earnings-cash flow regression. The overall result of the study shows that the application of IFRS improved information comparability between companies only in Canada, while the same was not the case for Russian companies and the cross-country comparability. However, the study confirms an increase in the comparability level in the post-adoption period in such industries as Energy and Basic materials not only between companies inside of the given country but on the cross-country level as well.

Viscoelastic or Viscoplastic Glucose Theory (VGT #46): Using Viscoplasticity/ Viscoplasticity to Explore the Inter-Relationships on CVD Risk % Versus Sensor Measured Fasting Plasma Glucose and Body Weight Based on Eight Collected Semi-Annual Data over an ~4-Year Period from 5/8/2018 to 3/20/2022 using the GH-Method: Math-Physical Medicine (No. 631)

The purpose of this research article is to explore a possible link between CVD risk probability percentage (CVD %) and body weight (BW) in the early morning. Body weight is very easy to measure by standing on a weight scale. Weight in the early morning is highly correlated with fasting plasma glucose (FPG) measured in the early morning or averaged glucose during sleeping hours. FPG also serves as the baseline of postprandial plasma glucose (PPG) and contributes around 25% to 29% of daily average glucose (eAG). Daily average glucose levels or quarterly HbA1C values (averaged eAG during the past 90-115 days) determine the severity of diabetes disease. Finally, diabetes is one of the major influential chronic diseases for developing many kinds of heart diseases, such as cardiovascular diseases (CVD). From the author’s mathematical view, in this biomedical field, an output biomarker sometimes turns into an input biomarker of a third biomarker. Therefore, many biomedical problems can be described as a scenario of the matrix with “m by n by p” dimensions. Since 2012, the author has been collecting his body weight (BW) and finger-piercing glucose values each day. In addition, he accumulates medical conditions data including blood pressure (BP), heart rate (HR), and blood lipids along with lifestyle details (LD). Based on the collected big data, he further organized them into two main groups. The first is the medical conditions group (MC) with 4 categories: weight, glucose, BP, and blood lipids. The second is the LD group with 6 categories: food & diet, exercise, water intake, sleep, stress, and daily routines. At first, he collected his data daily since Y2012 and then calculated a unique combined daily score for each of the 10 categories within the MC and LD groups. The combined scores of the 2 groups, 10 categories, and 500+ detailed elements constitute an overall “metabolism index (MI) model”. This MI model includes the root causes from 6 major lifestyle inputs and symptoms from 4 rudimentary chronic diseases: obesity, diabetes, hypertension, and hyperlipidemia. Therefore, it can serve as the foundation and building block for his additional research work that can expand into various diseases associated with different organs, such as cardiovascular diseases (CVD), and cancers.

Global and local economic uncertainties and office vacancy in Australia: a sub-class analysis

ABSTRACT Motivated by uncertainties caused by the COVID-19 pandemic, this study examines how office vacancy ratios (for premium, A, B, C and D-grade spaces) in Australia respond to shocks in global and local economic uncertainties. Using semiannual data from 1998 to 2020 and applying the vector autoregression (VAR) model, our results suggest that office vacancy ratios respond positively to economic uncertainty shocks in general, and especially to local economic uncertainty. Moreover, our sub-class analyses show that vacancy ratios in various office spaces respond differently to uncertainty shocks. The office vacancy ratio in premium-grade office responds to both shocks after one year with its responses fading out in year three. B-grade and C-grade vacancy ratios respond to both shocks within the first year and responses last for about 4 years. Additionally, sub-lease vacancy ratios in the aggregate office space show quick responses to uncertainty shocks (dying out in 2 years), while direct vacancy ratios respond after about 1 year (but fading out in 3 years).

The Risk-Taking Behaviour of Tunisian Banks in the Post-Revolution Era: A Panel ARDL-PMG Approach

This study investigates the long-term determinants of capital buffers and risk-taking adjustment by focusing on a sample of listed Tunisian commercial banks. This research uses hand-collected semi-annual data. The panel autoregressive distributed lags technique is used to control for unit root processes and to check for long-term determinants of capital and risk-taking adjustment. The empirical findings prove the existence of a moral hazard and procyclical behaviour of Tunisian banks in response to capital requirements. However, some results indicate that capital standards are still an important prudential tool for ensuring the robustness of Tunisian banks. There have been no previous studies focusing on this issue in the context of the Tunisian banking system in the turbulent post-revolution era. This paper innovates by assuming that a set of bank-specific, macroeconomic and regulatory variables exert a long-term rather than a short-term influence on capital buffers and risk-taking. The research does not consider a possible long-term simultaneous relationship between capital and risk-taking. The sample could be extended if data were available. Tunisian banks are advised to diversify their sources of revenues and to thoroughly revise their business models in order to become less dependent on revenues from traditional intermediation activities and to reduce the procyclicality of the banking system.

The Impact of IFRS 9 on the Link Between Lending and the Capital Ratio in Publicly Traded Banks in Poland

This paper aims to determine the role of the expected credit loss approach as defined in IFRS 9 in the effects of capital ratio on loans growth in publicly traded banks in Poland. To resolve this problem, we apply semi-annual data of individual banks in 2012–2018. Using several estimation techniques, we find that in the period of implementation of the expected credit loss approach, the links between loans growth and the capital ratio were enhanced. In particular, lending growth is more sensitive to levels of the capital ratio. These results are important with respect to the goal of bank financial stability and have implications for the conduct of macroprudential policy.

PDRB Sektor Pariwisata Terhadap Penyerapan Tenaga Kerja Di Provinsi Jawa Tengah : Analisis Cobb Douglas

This study aims to analyze the influence of the tourism sector's GDP on employment in Central Java Province. The research method uses, Return to Scale Analysis, and Elasticity Analysis on Cobb Douglas Regression. This research data is secondary data in the form of a time series for a period of 15 (fifteen) years, starting from 2005 to 2019, which is represented in semi-annual data. The results show that there is a positive and very significant influence of the tourism sector GRDP variable on the employment of Central Java Province. The GRDP of the Tourism Sector is the dominant variable in increasing the employment of Central Java Province.

Impact of Macroeconomic Variables, American Stock Market Index and Covid-19 Pandemic on Indonesia Capital Market Development (Time Series Study 1990-2020)

The purpose of this study is 1.) To analyze the influence of foreign investment on the development of the Indonesian capital market. 2).To analyze the influence of the Exchange Rate on the Development of the Indonesian Capital Market. 3).To analyze the influence of the Interest Rate on the Development of the Indonesian Capital Market. 4).To analyze the influence of the Dow Jones Stock Market Index on the Development of the Indonesian Capital Market. 5).To analyze the influence of the Covid-19 Pandemic (dummy variable) on the Development of the Indonesian Capital Market.6). In this study, secondary data and library research were used as a technique for collecting data, using semi-annual data for the period 1990-2020. The research was processed using the EViews 11 program with the multiple linear regression method. The results of the research are known if 1.) Foreign Direct Investment has a significant and positive effect on Capital Market Development. 2.) Exchange Rates have a significant and positive influence on the Development of the Indonesian Capital Market. 3.) Interest Rates have a significant and negative effect on the Development of the Indonesian Capital Market. 4.) The Dow Jones Stock Market Index has a significant and positive effect on the Development of the Indonesian Capital Market. 5.) The Covid-19 pandemic had a significant and negative effect on the Development of the Indonesian Capital Market in the period 1990 to 2020. The results of this study are expected to contribute to policy holders regarding the role of macroeconomic variables on the development of the capital market, so that in the future it can be one of the references in conducting the policy mix so as to improve the development of the Indonesian capital market.

Using Regression Analysis Model to Explore the Relationship Between the Finger-Piercing Fasting Plasma Glucose at the Wake-Up Moment and Body Weight in the Early Morning over a 6.5-Year Period for a type 2 Diabetes Patient Based on GH-Method: Math-Physical Medicine (No. 556)

The author began measuring his body weight at his wakeup moment in the early morning every day since 1/1/2012. In addition, he also measured his finger-piercing fasting plasma glucose (FPG) at the wakeup moment in the early morning starting on 1/1/2014. By early 2017, he noticed that there was a tight connection between his finger-piercing FPG and body weight with correlation coefficients from 80% to >90%. Therefore, he decided to use his finger FPG as the dependent variable Y and weight as the independent variable X to conduct a space-domain regression analysis over a long period of 6.5-years from 7/1/2015 to 11/24/2021. In this particular article, he compared the regression analysis results by using his semi-annual average data of both finger FPG and body weight. In summary, his finger FPG and Weight have an exceptionally high correlation of 92% with a variance of 84% using 13 semi-annual data over a period of ~6.5-years. Therefore, his regression predicted FPG and measured finger FPG also have a high variance of 84%. The regression analysis results matched his previous findings regarding weight and FPG since 2017. The regression predicted finger FPG equation is: Predicted finger FPG (Y) = 4.314 * weight (X) - 629.336 The significance F and p-value are extremely small which means that the data used in this study are statistically significant. Therefore, in the future, the author can guesstimate the fasting glucose value once he knows his body weight.

The Relationship Between Inflation and Unemployment in Namibia Within the Framework of the Phillips Curve

This study intended to empirically validate the applicability of the Phillips Curve in Namibia since independence, using semi-annual time series data, and taking into account the periods of the annus horribilis of the global financial crises and the Coronavirus Disease pandemic. It further sought to examine the nature of the relationship between inflation and unemployment to determine whether it is short-run or long-run and establish the causal relationship between the variables using various econometric analyses. The unit root tests indicate that the variables were stationary in their level forms, implying the absence of the long-run relationship. Hence, the Ordinary Least Square (OLS) model was performed to measure the short-run relationship between the variables. Results from the OLS analysis reveal a bidirectional nexus between inflation and unemployment, validating the presence of the Phillips Curve in the Namibian economy. These results correspond to the findings that incorporated the periods of economic shocks; thus, adjudging the critics of the Philips Curve regarding the consideration of economic shockwaves to be nonsensical in the Namibian economy. Finally, Granger causality test was conducted to establish the causal relationship between the variables, and results found inflation and unemployment to be unrelated. Based on these findings, the study recommends policymakers to adopt a policy mix, skewed to reducing unemployment predominately among the youth since the issues cannot be addressed simultaneously. Lastly, the study suggests future investigations to assess panel analyses on the phenomenon concerning developing countries, particularly those in the same region. It also recommends a significant focus on the determinants of inflation and unemployment since the variables were found to be independent of each other. This will give accurate directives to policymakers in an attempt to address the matter in terms of policy formulation and assimilation when they understand where the issue is deriving from.

Determinant of Residential Property Price Index in Five Asian Emerging Market Countries: A Demand and Supply Approach

This study aims to analyze the factors influencing the Residential Property Price Index (RPPI) from the demand and supply sides in five Asian emerging market countries. The data used are semi-annual data from the first semester of 2009 until the second semester of 2019 because this study aims to denote the impact of RPPI toward the demand and supply indicators after the global crisis in 2008. The dependent variable of this study is the RPPI, while the independent variables include the number of workers, real interest rate, economic growth, and the Real Effective Exchange Rate (REER). The Fixed Effects Model (FEM) is thus the applied method to process the data. In the end, the results indicate that all independent variables are significant toward the RPPI. The number of workers, real interest rate, and REER negatively affect the RPPI, while economic growth positively affects the RPPI.

Linkages between Effective Internal Control and Evaluating Market Risk Via Beta CAPM of Listed Banks in Vietnam Under Macro Effects During Pre-Low Inflation Period - Case of VCB, STB and ACB

This research paper aims to figure out and make comparison on how much effects in the market risk of two big listed Vietnam commercial bank, VCB and STB with semiannual data. Through using analysis, synthesis statistics methods, and dialectical materialism method, combined with econometric model with 9 macro variables, we figure out that CPI and GDP growth, lending rate and risk free rate (Rf) have much more impacts on market risk while external factors such as exchange rate and SP500 just have small effect on beta CAPM. Then, one of its major findings is the suggestion of macro and risk management policies for bank and relevant government agencies. Our recommendation can be used for reference in many other developing markets.

Better Management of Listed Banks in Vietnam for Sustainability During Pre-Low Inflation Period- Case of Sacom Bank (STB)

Further researches on banking industry to suggest bank policies and macro policies for sustainable development is becoming necessary.One of our purposes is to evaluating how much impacts in the market risk of a big listed Vietnam commercial bank, Sacombank- STB with semiannual data. It will serve for better management of bank and will contribute for sustainable economic development.Our traditional methods still be with qualitative analysis including synthesis and inductive, combined with OLS for 9 macro variables, findings show CPI and GDP growth, rate of loans and risk free rate (Rf) will put more impacts on market risk while external indicators (exchange rate and SP500) just put tiny effect on beta CAPM.This study can be functioned as references for further researches in other markets.

Management Strategy for Business Sustainability Under Macro Effects In An Econometric Model – Case of PKN Orlens in Oil and Gas Industry in Poland

The Poland economy has gained lots of achievements esp. in gas and oil industry during the 2014-2019 period and affected by Covid 19 and US-China trade war. Orlens group is a big gas and oil group operating in Central Europe countries such as Germany, Poland, Czech and Lithuania. This paper measures the revenue and EBITDA of a big gas and oil company, PKN Orlens in Poland, under impacts of macro indicators. As we experienced role of business management and sustainable development in gas and oil industry has been increasing with new perspectives in management, corporate governance models.In order to recommend for sustainable business development, this research paper aims to figure out how much effects in revenue from macro indicators of one of big listed Poland firms, PKN Orlens during the period 2014-2019 with semiannual data. Our findings show that revenue are affected much more by exchange rate and lending rate. It implies bank system policies and macro policies.

Enhancing risk management culture for sustainable growth of Asia commercial bank -ACB in Vietnam under mixed effects of macro factors

For sustainable growth, macro policy makers will need to look at risk management in banking industry and impacts of macro factors on market risk in order to adjust policies and build risk management culture in banking system. What we need to adjust in trade balance, risk free rate and other policies? This is one of reasons for us to conduct this study.This paper measures the Beta CAPM in famous model under impacts of both macro internal and external variables during low inflation time 2015-2020 in the country. The evidence is the fundamental role of risk management in commercial bank has been increasing with new perspectives in management, corporate governance and risk management models. We will estimate effects in risk measurement of one of big listed Vietnam commercial bank, Asia commercial bank (ACB) during the low inflation period 2015-2020 with semiannual data. Through using analysis, synthesis statistics methods, and dialectical materialism method, combined with econometric model with 9 macro variables, we figure out that CPI has a positive correlation with Beta CAPM of ACB, while Risk free rate (Rf) and lending rate have negative correlation with Beta CAPM of the bank. It implies that increase in inflation, together with decrease in Rf and lending rate will increase market risk.Then, one of its major findings is the suggestion of macro and risk management policies for bank and relevant government agencies. Our recommendation can be used for reference and expand researches in many other emerging markets.