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Record W2804830979 · doi:10.5430/ijfr.v9n3p26

The Impact of Tax Deduction Ratio Reduction on Dividend Payouts Under the Integrated Tax System: Evidence From Taiwan

2018· article· en· W2804830979 on OpenAlexvenueno aff
Sue-Tzeng Chuang, Ying-Hsiang Chen, Ching‐Chieh Lin, Wen‐Chih Lee

Bibliographic record

VenueInternational Journal of Financial Research · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsDividend payout ratioDividendDividend taxMonetary economicsEconomicsTax creditBusinessTax reformDouble taxationDividend policyFinanceState income taxPublic economicsGross income

Abstract

fetched live from OpenAlex

Taiwan passed the Robust Financial Administrative System in 2014. Regarding the imputation tax system, the tax credit of imputation was reduced from 100% to 50%, effective in 2015. In other words, contrary to the year 2014, only the half of tax paid by companies can be used by individuals to offset personal income taxes under the new system. The purpose of this study is to investigate whether dividend payouts are influenced by this tax reform. In addition, whether the companies known for stable dividends have changed their dividend payout ratios. Results show that the dividend payout ratios decreased after the tax reform was reduced, indicating that companies used this tax reform to enact tax planning for stockholders. This study also finds that companies offering stable dividends maintain similar dividend policies in the dividend payout ratios.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.038
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.085
GPT teacher head0.367
Teacher spread0.282 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

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