The Role of Auditors, Non-Auditors, and Internal Tax Departments in Corporate Tax Aggressiveness
Bibliographic record
Abstract
ABSTRACT Using confidential data from the Internal Revenue Service on who signs a corporation's tax return, we investigate whether the party primarily responsible for the tax compliance function of the firm—the auditor, an external non-auditor, or the internal tax department—is related to the corporation's tax aggressiveness. We report three key findings: (1) firms preparing their own tax returns or hiring a non-auditor claim more aggressive tax positions than firms using their auditor as the tax preparer; (2) auditor-provided tax services are related to tax aggressiveness even after considering tax preparer identity, which supports and extends prior research using tax fees as a proxy for tax planning; and (3) Big 4 tax preparers, in particular, are linked to less tax aggressiveness when they are the auditor than when they are not the auditor. Our findings help policymakers and researchers better understand an important feature of tax compliance intermediaries; particularly, how the dual role via audits is related to observable corporate tax outcomes.
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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 | 0.005 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".