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Public Finance in the Real World: Through the Lens (Down the Rabbit Hole?) of Transfer Pricing

2022· article· en· W4321513671 on OpenAlexvenueno aff
Scott Wilkie, Lorraine Eden

Bibliographic record

VenueCanadian Tax Journal/Revue fiscale canadienne · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Taxation and Avoidance
Canadian institutionsnot available
Fundersnot available
KeywordsTransfer pricingBase erosion and profit shiftingEconomicsMultilateralismSovereigntyMultinational corporationPublic financeFinanceInternational financeTax reformTax avoidanceInternational tradeDouble taxationPublic economicsPolitical scienceMacroeconomicsLawPolitics

Abstract

fetched live from OpenAlex

The current lack of confidence in the international rules for taxing the global profits of multinational enterprises (MNEs) has three underlying causes: (1) tax rules are not universal or natural; (2) taxes must be practical, administrable, and collectible; and (3) tax policy is a domain where national sovereignty and multilateralism are both important and conflictual. As a result, in the real world of public finance, the principles and norms of international tax must be tempered with the need for practicality and respect for national sovereignty. Transfer pricing, which affects how an MNE's global profits are allocated among countries, provides a good illustration of the difficult problem of implementing public finance principles and norms in the real world. Criticisms of the arm's-length principle have led the Organisation for Economic Co-operation and Development to recommend formulary approaches to transfer pricing in the pillar 1 and 2 proposals of its base erosion and profit shifting project. Instead, we propose a solution that draws its inspiration from the distinction made by the International Centre for Settlement of Investment Disputes between "investment" and "trade" that underlies the four-factor <i>Salini</i> test: contribution, assets, risk, and duration. We argue that the <i>Salini</i> test provides useful insights into the conundrum of "source" and a way out of the current lack of confidence in the international tax system. Our work builds on, and pays homage to, Richard Bird's lifelong contributions to public finance.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.648
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.040
GPT teacher head0.198
Teacher spread0.158 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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Same venueCanadian Tax Journal/Revue fiscale canadienneSame topicCorporate Taxation and AvoidanceFrench-language works237,207