Does Public Country‐by‐Country Reporting Deter Tax Avoidance and Income Shifting? Evidence from the European Banking Industry*
Bibliographic record
Abstract
ABSTRACT In this study, we examine the effect of increased tax transparency on the tax planning behavior of European banks. In 2014, the European Union introduced public country‐by‐country reporting requirements to the banking industry. Treating this new requirement as an exogenous shock, we find limited evidence consistent with a decline in income shifting by the banks' financial affiliates in the post‐adoption period (starting from 2015). We do not, however, find robust evidence of a significant change in the consolidated book effective tax rates among the affected banks. Our findings suggest that increased transparency from public country‐by‐country reporting can deter tax‐motivated income shifting but that it did not appear to materially influence the banks' overall tax avoidance. Our findings have policy implications for the ongoing debate between the European Parliament, the Organisation for Economic Co‐operation and Development, and accounting standard‐setting bodies on whether to require multinationals to publish country‐by‐country reports.
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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 | 0.007 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
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".