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Record W1487580352 · doi:10.3386/w15091

Do Multinationals or Domestic Firms Face Higher Effective Tax Rates?

2009· report· en· W1487580352 on OpenAlexaboutno aff
Kevin Markle, Douglas A. Shackelford

Bibliographic record

VenueNational Bureau of Economic Research · 2009
Typereport
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Taxation and Avoidance
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessFace (sociological concept)International economicsCorporate taxMonetary economicsInternational tradeEconomicsTax avoidanceDouble taxationFinance

Abstract

fetched live from OpenAlex

To our knowledge, this paper provides the most comprehensive analysis of firm-level corporate income tax expenses to date. We use publicly available financial statement information to estimate firm-level effective tax rates (ETRs) for 10,642 corporations from 85 countries from 1988 to 2007. We find that multinationals and domestic-only companies face similar ETRs. We also find that, on average, ETRs declined by seven percentage points or 20% over the period. German, Japanese, Australian and Canadian decreases were large. American, British, and French declines were more modest. Nonetheless, because ETRs were falling worldwide, the ordinal rank from high-tax countries to low-tax countries changed little. Japanese firms always faced the highest ETRs. ETRs for tax havens and countries from the Middle East and Asia (ignoring Japan) were always lower than those for the U.S. and European countries. These findings should provide some empirical underpinning for ongoing policy debates about the taxation of multinational profits.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient 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: Other · Consensus signal: none
Teacher disagreement score0.894
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.263
GPT teacher head0.489
Teacher spread0.226 · 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
GenreOther

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

Citations26
Published2009
Admission routes1
Has abstractyes

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