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Record W2137669226 · doi:10.1108/20408741111178799

Institutional environment, inside ownership and effective tax rate

2011· article· en· W2137669226 on OpenAlexaff
Tao Zeng

Bibliographic record

VenueNankai Business Review International · 2011
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Taxation and Avoidance
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsOriginalityBusinessChinaSample (material)Value (mathematics)Tax rateCorporate taxEmpirical evidenceAccountingMonetary economicsPublic economicsTax avoidanceEconomicsDouble taxationFinance

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to examine the effect of institutional environment and inside ownership on the tax reporting practices of Chinese listed firms. Design/methodology/approach It is an empirical study using a sample of Chinese listed firms for eight years of time periods between 1998 and 2005. Findings This study finds that in Chinese provinces with more developed institutions, firms have higher effective tax rates; however, firms with inside ownership in these regions have lower effective tax rates. Further analysis shows that the above results hold only for non‐state‐owned firms. Originality/value The paper presents the first study of the impact of inside ownership and institutional environment on corporate effective tax rate in China.

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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.682
Threshold uncertainty score1.000

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)0.0020.001

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 head0.034
GPT teacher head0.225
Teacher spread0.191 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations17
Published2011
Admission routes1
Has abstractyes

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