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Record W4210991435 · doi:10.33423/jabe.v24i1.4949

Dividends, Return and Consumption

2022· article· en· W4210991435 on OpenAlexvenueno aff

Bibliographic record

VenueJournal of Applied Business and Economics · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing Market and Economics
Canadian institutionsnot available
Fundersnot available
KeywordsEconomicsDividendDividend yieldStock (firearms)Equity (law)Monetary economicsEmpirical evidenceEmpirical researchConsumption (sociology)Rate of returnCashFinancial economicsCash flowDividend policyFinance

Abstract

fetched live from OpenAlex

Based on empirical evidence, households consume dividends from common stock at a much higher rate than the rise in its price. This pattern is consistent with consumption from durable, predictable, and permanent sources of income as compared with non-durable income. Such a separate tracking of dividends and capital gains is not consistent with the notion of return as the combination of both: price appears to convey performance as compared to return. Empirical studies show that dividend yield predicts return in the short and the long horizons, particularly when the effects of repurchase activities as well as cash flow transfers to equity holders are included. The various empirical findings show, in part, that the market price of the stock does not decline as a result of the payment of cash dividend by as much as the elegant hypothesis of Miller and Modigliani implies. Behavioral finance provides some explanations in this regard as investors appear to view dividends as given, and place it in a mental account separate from the rise in price of the stock and not as an integral part of return.

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)0.000
metaresearch head score (Gemma)0.006
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 score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.006
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 science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.024
GPT teacher head0.189
Teacher spread0.165 · 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
Published2022
Admission routes1
Has abstractyes

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