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Career Concerns of Top Executives, Managerial Ownership and CEO Succession

2008· preprint· en· W3121728129 on OpenAlexaff
M. Martin Boyer, Hernan Ortiz Molina

Bibliographic record

VenueCorporate Governance An International Review · 2008
Typepreprint
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsUniversity of British ColumbiaUniversité de MontréalHEC Montréal
Fundersnot available
KeywordsInsiderPortfolioPromotion (chess)BusinessNominationBusiness administrationManagementEconomicsFinancePolitical science

Abstract

fetched live from OpenAlex

ABSTRACT Manuscript Type: Empirical Research Question/Issue: We hypothesize that a top manager's stock ownership in the firm signals to the board information about his or her privately known ability to run the company. As a consequence, the outcome of a CEO succession is affected by the managers’ ownership choices, which therefore depend on their career concerns. Research Findings/Results: Our study of CEO turnover events in US firms provides support for our basic hypothesis. Specifically, we find that (1) lower insider ownership makes outside CEO succession more likely; (2) higher ownership by an insider increases his or her chances of promotion; (3) non‐appointed managers with higher ownership are more likely to reduce their ownership stake or to leave the firm following CEO succession; and (4) ownership reduction and departure decisions are more likely following outside CEO appointments. Theoretical Implications: Consistent with signaling theory, our analysis suggests that (1) managerial ownership plays a role in resolving asymmetric information problems between top managers and the board of directors in the context of CEO succession, and (2) managers’ portfolio decisions and their departure decisions are driven in part by their career opportunities in the firm. Practical Implications: By monitoring managerial ownership decisions surrounding CEO turnover, boards of directors can acquire information about the potential candidates’ ability to run the firm and thus better identify the best successor. As managers can more easily signal their information to the board when their ownership choices are observable to the public, security laws that encourage the disclosure of managers’ beneficial ownership stakes may increase the efficiency of boards’ choices and firm 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 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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.403
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.001
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 head0.081
GPT teacher head0.283
Teacher spread0.202 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations1
Published2008
Admission routes1
Has abstractyes

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