Transparency, Information Shocks, and Tax Avoidance
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT This study helps provide clarity to the prior mixed findings on the association between financial reporting transparency and tax avoidance by studying the effect that transparency has on tax avoidance in a cross‐country sample through aggregate‐ and firm‐level tests. Results using firm‐ and country‐level (aggregate) measures of transparency and tax avoidance show that countries and firms with greater levels of transparency exhibit lower levels of tax avoidance and that the effect of country‐level transparency is incremental to firm‐level transparency. Furthermore, results of difference‐in‐difference tests using the adoption of IFRS and the initial enforcement of insider trading laws around the world as exogenous shocks that increase transparency find that transparency has a statistically and economically significant effect on tax avoidance and address empirical concerns regarding endogeneity and reverse causality not fully addressed in the prior research. The results of these tests as well as tests that address potential correlated but omitted variables suggest that financial transparency is an important tool which regulators can use in battling tax avoidance.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.007 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 it