Do SWF investments matter for bond ratings? The role of corporate governance
Bibliographic record
Abstract
Abstract We investigate the impact of sovereign wealth funds (SWFs) equity ownership on bonds’ credit ratings of their target firms. Using a sample of 2045 bonds issued by 324 SWF target firms from 16 countries over the period 1996–2020, we find evidence linking SWF investments to lower likelihood of bond rating upgrades. Consistent with value‐reducing political agenda hypothesis, our results suggest that credit rating agencies perceive SWFs as a structure that could affect the quality of corporate governance and harm bondholder interests by leaving them vulnerable to losses. Our results also show that credit rating could be improved: (i) with SWF transparency and experience; (ii) when SWFs take a more passive investment stance; and (iii) within the financial crisis period. Finally, and interestingly, using generalized structural equation modelling, we provide evidence supporting the mediating role of target firm's corporate governance quality in the relationship between SWF investments and bond ratings. Our findings are robust to controls for the endogeneity and heteroscedasticity issues and to alternative sample compositions and regression frameworks.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".