Impact of Ownership Structure on Firm Performance in the MENA Region: An Empirical Study
Bibliographic record
Abstract
This paper investigates the impact of ownership structures on firm financial performance in the MENA region. The sample covers nine MENA countries (Egypt, Bahrain, Qatar, Kuwait, Tunisia, UAE, Morocco, Oman and Jordan) for the year 2014. We examine the impact of ownership structures on firm performance. Performance is proxied by Tobin-Q, ROE and ROA, while ownership structure is proxied using insider ownership, governmental, and blockholders. We control for risk, size, country effect and industry type. Our results suggest that blockholders, insider ownership and governmental ownership play a crucial role in firm performance measured by Tobin-Q, ROE and ROA respectively. Our results suggest that insider ownership negatively effects firm’s return on equity, while blockholder ownership has a positive impact on a firm’s Tobin-Q. Finally we find that governmental ownership plays a positive role on a firm’s return on assets in the MENA region.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".