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Record W2884690621 · doi:10.2308/accr-52194

Tax Uncertainty and Incremental Tax Avoidance

2018· article· en· W2884690621 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Accounting Review · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Taxation and Avoidance
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsTax avoidanceEconomicsMonetary economicsTax rateTax creditPublic economics

Abstract

fetched live from OpenAlex

ABSTRACT We investigate whether tax avoidance becomes more uncertain as the rate of tax avoidance increases. We estimate a system of equations to demonstrate that as firms' pretax income increases, each additional dollar of potential tax results, on average, in 32.8 cents of tax avoided, which we refer to as incremental tax avoidance. Of the incremental tax avoided, 1.4 cents represent additions to the reserve for uncertain tax benefits (UTB reserve), or 4.3 percent of the total incremental tax avoided. We then partition sample firms into groups that prior research suggests engage in higher rates of tax avoidance, and examine the amount of incremental tax avoidance that results in additions to the UTB reserve. Results demonstrate that the percentage of incremental tax avoidance reflecting additions to UTB reserve is not larger for groups engaging in higher rates of tax avoidance, suggesting higher rates of tax avoidance may not be more uncertain. JEL Classifications: H26; M41; M48.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.448
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.022
GPT teacher head0.249
Teacher spread0.227 · 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