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Record W2999906423 · doi:10.1111/1911-3846.12587

The Role of Pension Business Benefits in Institutional Block Ownership and Corporate Governance*

2020· article· en· W2999906423 on OpenAlexvenueno aff
Jing Huang, Steven R. Matsunaga, Zhibin Wang

Bibliographic record

VenueContemporary Accounting Research · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsPensionCorporate governanceBusinessShareholder valueValue (mathematics)Shock (circulatory)Institutional investorAccountingShareholderFinanceLabour economicsEconomics

Abstract

fetched live from OpenAlex

ABSTRACT We investigate whether potential pension contracting benefits lead institutions that provide pension services to acquire ownership blocks in firms and the implications of such blockholdings on the firms' corporate governance. We use the 2006 Pension Protection Act, which expanded pension participation in certain states, as a quasi‐exogenous shock and find an increase in block ownership by pension‐providing institutions in firms with substantial operations in affected states. Further, we find that the acquisition of a large block increases the likelihood that the institution will provide future pension services to the firm. With regard to corporate governance, we find that the acquisition of large pension blockholdings is associated with higher CEO pay and lower CEO turnover following poor financial performance. However, contrary to the prediction of the private benefits hypothesis, we do not find consistent evidence that large pension blockholdings are associated with declining firm profitability, suggesting that pension institutions are incentivized to exert monitoring to preserve the investment value of their blockholdings. Overall, our evidence is consistent with pension service institutions acquiring ownership blocks to obtain pension contracts, but our evidence does not support the prediction that they use their influence to compromise shareholder value.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.095
GPT teacher head0.261
Teacher spread0.166 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2020
Admission routes1
Has abstractyes

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