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Record W4313584320 · doi:10.5539/ijef.v15n2p18

Parachute Effect of Dividends Paid in Times of Health Crisis: Case of Moroccan MSI 20 Companies

2023· article· en· W4313584320 on OpenAlexvenueno aff
Hajar BENJANA

Bibliographic record

VenueInternational Journal of Economics and Finance · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsShareholderDividendDividend policyOrder (exchange)Profit (economics)BusinessStock (firearms)Distribution (mathematics)Stock marketMonetary economicsEconomicsFinancial systemFinanceCorporate governanceMicroeconomicsMathematics

Abstract

fetched live from OpenAlex

The dividend is a part of the profit that remunerates the shareholder, but in the deeper sense it is a tool that aims to cement at first sight the relationship between the company and its shareholders within the framework of a Shareholder Relationship Management (SRM). Indeed, the dividend is dependent on the choice of the company, its size, its sector of activity but also on the economic situation of the country. Moreover, in times of crisis, some listed companies waive this distribution and others, on the other hand, seem more generous to absorb the fall in the stock market prices of their values in order to appease the losses suffered by their shareholders. In doing so, the objective of this research is to analyze the dividend distribution policy of listed companies who form the MSI 20 in order to verify the existence of the parachute effect of the dividend. For that, we choose a five-year study running from 2017 to 2021.

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)0.004
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 score0.062
Threshold uncertainty score0.124

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.019
GPT teacher head0.252
Teacher spread0.233 · 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
Published2023
Admission routes1
Has abstractyes

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