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Record W3019911512 · doi:10.1561/108.00000043

Which Aspects of Corporate Governance Do and Do Not Matter in Emerging Markets

2020· article· en· W3019911512 on OpenAlexaff
Bernard S. Black, Antônio Gledson de Carvalho, Vikramaditya S. Khanna, Woochan Kim, B. Burçin Yurtoğlu

Bibliographic record

VenueJournal of Law Finance and Accounting · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsKellogg's (Canada)
Fundersnot available
KeywordsCorporate governanceEmerging marketsAccountingShareholderBusinessIndex (typography)Independence (probability theory)Value (mathematics)Control (management)EconomicsFinanceManagement

Abstract

fetched live from OpenAlex

Well-constructed, country-specific “corporate governance indices” can predict higher firm values in emerging markets. However, there is little credible research on which aspects of governance drive that overall relationship. We study that question across four major emerging markets (Brazil, India, Korea, and Turkey). We build overall country-specific governance indices, comprised of indices for disclosure, board structure, ownership structure, shareholder rights, board procedure, and control of related party transactions. Disclosure (especially financial disclosure) predicts higher market value across all four countries. Board structure (principally board independence) has a positive coefficient in all countries and is significant in two countries. The other indices do not predict firm value. These results suggest that regulators and investors, in assessing governance, and firm managers, in responding to investor pressure for better governance, would do well to focus on disclosure and board structure.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.806

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.003
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 head0.017
GPT teacher head0.206
Teacher spread0.190 · 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.

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

Citations40
Published2020
Admission routes1
Has abstractyes

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