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Record W4406445764 · doi:10.1016/j.jacceco.2025.101765

Comply-or-explain regulation and investor protection

2025· article· en· W4406445764 on OpenAlex
Thomas Bourveau, Xingchao Gao, Rongchen Li, Frank Zhou

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

VenueJournal of Accounting and Economics · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsUniversity of Toronto
FundersErasmus Universiteit RotterdamUniversiteit van AmsterdamUniversity of Oklahoma
KeywordsInvestor protectionBusinessEconomicsMonetary economicsFinancial systemFinancial economicsFinanceCorporate governance

Abstract

fetched live from OpenAlex

We investigate a 2012 comply-or-explain regulation implemented by China’s Shanghai Stock Exchange. The regulation requires eligible firms to pay 30% of their current-year profits as cash dividends or explain the reasons why they do not meet this requirement through a public conference call. Using firms listed on the Shenzhen Stock Exchange as a control group, our difference-in-differences estimates suggest that firms subject to the regulation decreased tunneling, irrespective of whether they complied by paying or disclosing. Further analyses suggest that the reduction in tunneling is partially attributed to enhanced regulatory monitoring over explaining firms and the constraint on excess cash of paying firms. These findings offer novel policy insights into how a flexible comply-or-explain form of regulation can mitigate agency costs between controlling and minority shareholders in a weak institutional environment.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.231
Threshold uncertainty score0.274

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 head0.021
GPT teacher head0.199
Teacher spread0.178 · 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