Worldwide Corporate Income Taxes
Bibliographic record
Abstract
To our knowledge, this paper provides the most comprehensive analysis of firm-level corporate income taxes 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, on average, ETRs declined by seven percentage points or 20 % over the period with much of the decline occurring from 1992 to 1994. 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. The 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. For most countries, their multinationals and domestic-only companies face similar ETRs. These findings should provide some empirical underpinning for ongoing policy debates about the taxation of multinational profits.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".