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Record W4392562746 · doi:10.1111/fmii.12195

Do SWF investments matter for bond ratings? The role of corporate governance

2024· article· en· W4392562746 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFinancial Markets Institutions and Instruments · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicState Capitalism and Financial Governance
Canadian institutionsSt. Francis Xavier UniversityUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsCorporate governanceBusinessCorporate bondBondAccountingFinancial systemFinance

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.852
Threshold uncertainty score0.608

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.016
GPT teacher head0.217
Teacher spread0.201 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it