Efficiency performance and the insolvency risk for Takaful insurance firms: evidence from the Gulf Cooperation Council countries
Bibliographic record
Abstract
We utilise the data envelopment analysis (DEA) and the distance-to-default concept (Z-score) to examine the efficiency performance and the insolvency risk (IR) of 54 Takaful firms (TFs) in the Gulf Cooperation Council (GCC) countries. We also use the robust regression model to investigate the relationship between IR and its determinants. Results reveal that TFs are not fully efficient, and inefficiencies are large-scale. Poor management, to some extent, is the source of inefficiencies. Low allocative scores contribute to the firms' cost inefficiency, indicating that 'input proportions' do not guarantee the minimum possible cost. Room for improvement is evident by shrinking the operations and better managing the 'input resources' and 'output mix'. Moreover, efficiency is vital in determining the TFs' insolvency risk. Furthermore, we find Takaful firms were significantly and adversely affected by the 2008 global financial crisis but exhibited speedy recovery and an increasing trend in the efficiency scores.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".