Strategic Deviation and Corporate Tax Avoidance: A Risk Management Perspective
Bibliographic record
Abstract
We examine the association between strategic deviation—defined as the deviation of firms’ resource allocation from that of industry peers—and corporate tax avoidance. By combining the agency perspective with the risk aspect, we argue that managers of firms with high strategic deviation avoid tax compared with those of firms with low strategic deviation. High-strategic-deviant firms who avoid tax are likely to face the risk of compromising firm value. Based on a large sample of 40,168 US firm-year observations for the period 1987–2020, we find evidence supporting our hypothesis. A series of robustness tests validates our main finding. We further provide evidence to suggest that the positive association between strategic deviation and tax avoidance is stronger for deviant firms with high financial constraints, low institutional ownership, firms operating in more competitive markets, and procuring higher auditor provided tax services from incumbent auditors. Importantly, we show that the capital market penalises tax avoidance strategies undertaken by the deviant firms.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 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".