Does Ownership Structure Moderate the Relationship between Systemic Risk and Corporate Governance? Evidence from Gulf Cooperation Council Countries
Bibliographic record
Abstract
The objective of this paper is to empirically examine the moderating effect of ownership structure on the relationship between systemic risk and corporate governance. It complements prior research by studying the relationship between the proportion of capital held by state institutions and systemic risk. It also examines the internal governance mechanisms that mitigate systemic risk. For this purpose, this research used a dataset consisting of 22 banks from Gulf Cooperation Council (GCC) countries (10 Islamic banks and 12 conventional banks) over the period 2004–2018. We used a three-stage least squares (3SLS) regression to test our research hypotheses. The findings revealed that the structure of the board of directors (BOD) reduced systemic risk in the banking sector. In particular, we provide evidence that board composition and board meetings negatively affect systematic risk. In addition, we provide empirical evidence that the state plays a key role in moderating the relationship between governance mechanisms and systemic risk. As such, our paper provides significant contributions to the governance and corporate finance literature.
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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 | 0.002 | 0.006 |
| 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 | 0.001 |
| 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".