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The Transfer-Pricing Profit-Split Method After BEPS: Back to the Future

2019· article· en· W2997018012 on OpenAlexvenueno aff
Michael Kobetsky

Bibliographic record

VenueCanadian Tax Journal/Revue fiscale canadienne · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Taxation and Avoidance
Canadian institutionsnot available
Fundersnot available
KeywordsTransfer pricingBase erosion and profit shiftingProfit (economics)PillarMicroeconomicsBusinessEconomicsIndustrial organizationPublic economicsFinanceEngineeringDouble taxationTax avoidance

Abstract

fetched live from OpenAlex

In 2018, the Organisation for Economic Co-operation and Development/Group of Twenty (OECD/G20) Inclusive Framework on base erosion and profit shifting (BEPS): action 10 issued revised guidance on the transactional profit-split method. Regrettably, the revised guidance failed to provide the opportunity for the profit-split method to be more often the most appropriate transfer-pricing method. The revised guidance expressly states that the lack of comparable uncontrolled transactions, by itself, is not a basis for the use of the profit-split method. Under the former guidance, the profit-split method was used infrequently. In the revised guidance, the threshold requirements for the use of the profit-split method are still restrictive. Consequently, it is likely that the profit-split method will rarely be the most appropriate transfer-pricing method. Nevertheless, the residual profit-split method is being considered for BEPS action 1, on the taxation of the digital economy. Two of the proposals under pillar 1 of the Inclusive Framework's 2019 short policy note involve the use of the residual profit-split method to allocate profits. These proposals involve new profit allocation rules that go beyond the arm's-length principle.

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)0.001
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.884
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 communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.008
GPT teacher head0.185
Teacher spread0.177 · 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

Citations2
Published2019
Admission routes1
Has abstractyes

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