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Record W2049837671 · doi:10.1108/ara-01-2014-0012

Earnings management around tax rate reduction: evidence from China's 2007 corporate tax reform

2014· article· en· W2049837671 on OpenAlexaff
Tao Zeng

Bibliographic record

VenueAsian Review of Accounting · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsEarnings managementAccrualBusinessAccountingLabour economicsEconomicsEarnings

Abstract

fetched live from OpenAlex

Purpose – The purpose of this paper is to examine earnings management around tax rate reduction in the wake of the 2007 corporate tax reform in China. Design/methodology/approach – This paper is an empirical work using a sample of listed Chinese real estate firms. Findings – This study finds that firms managed earnings, including accrual-based earnings management and real earnings management, to decrease income in the fourth quarter of 2007, and to increase income in the first quarter of 2008. It suggests that the real estate firms were shifting income from the fourth quarter of 2007, when the statutory tax rate was 33 per cent, to the first quarter of 2008, when the statutory tax rate was 25 per cent, and therefore saved on tax payments. It also finds that corporate ownership structures, including ownership concentration and state ownership, affect earnings management. In the fourth quarter, state ownership is negatively associated with accrual-based earnings management, while ownership concentration is positively related to both accrual and real earnings management. In the first quarter, state ownership is negatively related to real earnings management. Social implications – Tax authority and policy makers might be interested in evidence on earnings management around tax rate reduction. Changes in tax rates increase the incentives to shift income, which may warrant a closer scrutiny by both outside auditors and tax auditors. Originality/value – This paper is the first study that relates to both accrual-based earnings management and real earnings management to corporate tax rate changes by showing that firms manipulate income upward in the low-tax-rate periods and downward in the high-tax-rate periods.

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)0.004
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.769
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.004
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.002

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 head0.014
GPT teacher head0.229
Teacher spread0.215 · 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 teacher head, not a consensus.

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

Citations19
Published2014
Admission routes1
Has abstractyes

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