Parametric, Non-Parametric and Multivariate Analysis of Capital Structure During the Financial Crises in Jordanian Banks
Bibliographic record
Abstract
Motivations: This research seeks to analyze the determinants of capital structure of the banking sector in Jordan taking into consideration bank business model (Islamic versus Commercial bank). The research also sheds light on the financial crises of 2007/2008 and its impact on the financing decision in the banking sector.Novelty: Although the topic of capital structure's determinants is well studied in non-financial firms, very few studies considered the financial firms, namely banks. Since the nature of operations and capital components for banks are totally different this research comes to fill the gap in the banking literature.Methodology and Methods: The study uses multivariate regression techniques of panel data besides the parametric and non-parametric analysis. Three measurements of capital structure are considered: leverage ratio, long term debt ratio and short-term debt ratio, the explanatory variables are included in two sets, bank specific characteristics and economic characteristics.Data and Empirical Analysis: Balanced panel data set was formed for 27 Jordanian banks during the period of 2003-2015. Empirically, the findings suggest a variation of capital structure determinants based on the variable of measurement. However, the analysis confirms that bank's profitability and bank's risk are major components of the capital structure decision regardless of its measurement variable. In addition to these two variables, liquidity, growth and taxes are important variable in the short-term debt financing, and retained earnings is important to the long-term financing. Empirically proven that Jordanian banks' capital structure decision is affected by the global financial crisis 2007/2008 and by bank type. Jordanian banks might differ in size, but this doesn't affect their policies toward the capital structure. The empirical results are consistent with the pecking order theory that profitable firms prefer to use more of their internal sources of funds rather than debt financing.Policy Implications: Due to the importance of the capital structure decision for banks and non-banks firms and based on our finding, the policy makers in Jordan and may in other similar countries should pay attention to capital requirement regulations as the determinants of leverage among banks are different based on the business model whether commercial or Islamic.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".