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Record W3121280418 · doi:10.1111/fire.12078

The Global Preference for Dividends in Declining Markets

2015· preprint· en· W3121280418 on OpenAlexaboutno aff
Michael A. Goldstein, Abhinav Goyal, Brian M. Lucey

Bibliographic record

VenueFinancial Review · 2015
Typepreprint
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsnot available
FundersUS-UK Fulbright CommissionYale University
KeywordsDividendEmerging marketsEquity (law)Dividend policyFinancial economicsMonetary economicsShareholderEconomicsDividend payout ratioBusinessDividend yieldChinaFinancial crisisCorporate governanceFinance

Abstract

fetched live from OpenAlex

Abstract Investors globally prefer dividend‐paying stocks over nondividend‐paying stocks more in declining than in advancing markets, even accounting for firm‐level growth opportunities, size and risk effects. Dividend‐paying stocks outperform nondividend‐paying stocks, from 0.63% (China) to 3.79% (Canada) more per month in declining than in advancing markets. In declining markets, dividend‐paying firms outperform by more than any underperformance in advancing markets. The results are robust across dividend taxation regimes, legal environments, emerging and developed markets, periods prior to and after the 2008 global financial crisis, the exclusion of the dividend declaration month and in respect to segmented or integrated international capital markets.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.106
GPT teacher head0.309
Teacher spread0.203 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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