Impact of the Financial Crisis on Profitability of the Islamic Banks vs Conventional Banks- Evidence from GCC
Bibliographic record
Abstract
Using the data extracted from BankScope database of 92 banks in GCC (27 Islamic Banks and 65 Conventional Banks) for the period from 2006 to 2009, this study intends to investigate the impact of the financial crisis on the performance of both Islamic and conventional banks and test whether Islamic bank performance is better before and during the crisis.The study employs T-Test to observe any significant difference between Islamic and Conventional banks performance before and during the crisis.Three ratios were used to represent bank profitability measures which are return on assets (ROA), return on equity (ROE) and net interest margin (NIM) while two variables were used to measures each one of the bank-specific characteristics,: Equity and Tangible Equity as measures for Capital Structure, Loans and Liquid Assets as measures for Liquidity, and Deposits and Overheads for Liability. The results showed that the financial crisis had a negative impact on profitability of both Islamic and conventional banks but the Islamic banks were more profitable than conventional bank during the financial crisis but not statistically significant. The profitability determinants behaved differently for Islamic and conventional banks during the crisis. By applying the t-test it is found that the Islamic banks had better capital structure than the conventional banks during the financial crisis while the conventional banks had better liquidity and liability ratios than the Islamic banks. No strong statistical evidence found that Islamic banking has weathered the financial crisis than conventional counterparts in all performance measures.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".