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Record W2110434128 · doi:10.1257/002205105774431252

Corporate Governance, Economic Entrenchment and Growth

2004· article· en· W2110434128 on OpenAlexaff
Randall Mørck, Daniel Wolfenzon, Bernard Yeung

Bibliographic record

VenueJournal of Economic Literature · 2004
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCorporate governanceShareholderProperty rightsEnforcementBusinessPrivate benefits of controlPoliticsMarket economyControl (management)Capital (architecture)VotingMonetary economicsCapital marketEconomicsEconomic systemFinanceMicroeconomics

Abstract

fetched live from OpenAlex

Around the world, large corporations usually have controlling owners, who are usually very wealthy families. Outside the U.S. and the U.K., pyramidal control structures, cross shareholding and super voting rights are common. Using these devices, a family can control corporations without making a commensurate capital investment. In many countries, such families end up controlling considerable proportions of their countries'' economies. Three points emerge. First, at the firm level, these ownership structures vest dominant control rights with families who often have little real capital invested n creating agency and entrenchment problem simultaneously. In addition, controlling shareholders can divert corporate resources for private benefits using transactions within the pyramidal group. The result is a poor utilization of resources. At the economy level, extensive control of corporate assets by a few families distorts capital allocation and reduces the rate of innovation. The result is an economy-wide misallocation of resources, and slower economic growth.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.003
Scholarly communication0.0040.003
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.009
GPT teacher head0.181
Teacher spread0.172 · 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

Citations407
Published2004
Admission routes1
Has abstractyes

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