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Record W1532663458

Formulary Apportionment and Group Taxation in the European Union: Insights from the United States and Canada

2005· book· en· W1532663458 on OpenAlexaboutno aff
Joann Martens Weiner

Bibliographic record

Venuenot available
Typebook
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Taxation and Avoidance
Canadian institutionsnot available
Fundersnot available
KeywordsFormularyApportionmentEuropean unionPublic economicsScope (computer science)BusinessMember statesDouble taxationAccountingEconomicsEconomic policyPolitical scienceComputer scienceLawMedicine
DOInot available

Abstract

fetched live from OpenAlex

In 2001, the European Commission endorsed a future company tax strategy that would allow EU companies the option of calculating their EU profits on a common consolidated tax base and allow Member States to tax their share of that base at national rates. Implementing this strategy requires developing a formula to distribute the common tax base across the Member States. Although EU Member States currently do not use formulary methods to distribute a common consolidate tax base across national boundaries, Canada and the United States have extensive experience using formulary methods to distribute income across sub-national boundaries. Thus, the European Union can turn to North America to gain valuable insights into the design of a formulary apportionment system with common base taxation. This paper evaluates key issues that may arise when implementing common consolidated base taxation with formulary apportionment in the EU. These issues include the formula design, the definition of the company group and the definition and scope of the tax base. The paper also discusses potential economic consequences that may arise and suggests a potential apportionment system for the European Union.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.610
Threshold uncertainty score0.581

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.170
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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations32
Published2005
Admission routes1
Has abstractyes

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