Dynamic panel data analysis of the impact of governance on bank capital structure in Indonesia

Due to the uniqueness of the services sector in terms of its characteristics and profitability, as well as the lack of studies on this sector, this study is considered to be the first to improve the knowledge of the key factors that play an important role in the profitability of the Jordanian services sector. This study investigates the effect of financial characteristics and capital structure on the profitability of all 46 services companies listed on the Amman Stock Exchange over the period 2014–2018. This study applies fixed and random effects models to panel data variables, namely, size, tangible assets, growth, business risk, debt to equity ratio and debt to assets ratio as independent variables. At the same time, profitability was measured by operating profits (earnings before interest and tax divided by total assets), return on assets (ROA), and return on equity (ROE), which acted as the dependent variables. This study reveals the first evidence that the debt to assets ratio has a negative and significant impact on the profitability of services companies in Jordan. In line with the pecking order theory, this finding suggests that more profitable services companies tend to prioritize the use of retained earnings in financing business activities rather than in financing debt. This study shows that profitability is significantly and positively affected by size and business risk, while ROA is negatively affected by business risk. It also shows that tangible assets have a negative and significant effect on profitability, while growth has a positive and significant effect on operating profits.

The aim of the article was to find out the optimal capital structure of the companies in relation to their maximum performance. To reach this aim, the data of the companies operating in the field of heat industry of the Slovak Republic were used. As the first method, a correlation matrix was applied. It was found out that there is statistically significant relationship between capital structure indicators and performance of the companies. Due to the lack of data in time series, the authors were not able to apply multiple regression model to assess the impact of these indicators on performance. Therefore, a method of modelling was used to analyze the impact of the change in capital structure on performance. Modelling was based on the principle of a gradual change in the capital structure in favor of debt. By the increase in debt, it was confirmed that there was a change in the values of selected indicators. In the course of analysis, it was confirmed that the value of EVA equity increased with the rising indebtedness by which the proposition I of the modified MM theory was supported. The performance expressed by EVA entity indicator is at its minimum when the capital structure is 90:10 in favor of equity. By increasing the debt, EVA entity rises. Based on these results, it can be stated that the performance of selected companies increases when the share of debt also rises, even when taking into account the rising financial risks.

Managing capital structure is an imperative decision made by all firms. The manner in which financing is organized is a strategic financial decision and managers must settle on the amount of debt in relation to equity that it requires to maintain. Despite many empirical studies investigating the choice of capital structure for large corporates, minimal research has been conducted on capital structure decisions in small, medium, and micro enterprises (SMMEs). This study identifies major factors influencing the capital structure of SMMEs in a developing economy and enlightens owners/managers on the importance thereof. This investigation used a quantitative research approach, which was cross-sectional. A convenience sampling method was adopted, and data were collected from 136 respondents, only confined to the retail and whole sector, which is the second largest sector in KwaZulu-Natal, South Africa. The partial least squares structural equation modelling was utilized to determine the statistical results. It was discovered that managerial factors such as individual goals and financing preference of the owner/manager, network ties, attitude to debt, maintaining control and asymmetric information; and firm-level factors such as size of the firm, profitability and firm age are major factors that influence the capital structure of SMMEs. Therefore, capital structure decisions are made motivated by the attitudes of the owners/managers.