Two faces of product market competition and tax avoidance
Bibliographic record
Abstract
This paper investigates the effect of product market competition on a firm’s tax avoidance behavior. We develop a theoretical model showing that a greater product market competition could increase the managerial incentive of tax avoidance due to a “threat-of-punishment” effect but decrease shareholders’ incentive of tax avoidance due to a “value-of-tax-saving” effect, resulting in an inverted U-shape relationship between product market competition and tax avoidance. Moreover, the turning point of the inverted U-shape relationship is a function of a firm’s productivity and corporate governance. Empirically, we find consistent evidence that the effect of product market competition on a firm’s tax avoidance has an inverted U-Shape and such an effect varies across firms with different productivity and corporate governance. Our analysis highlights the complex effect of product market competition on a firm’s tax avoidance activities. Valuation Insight: As product market competition increases, tax avoidance by firm first increases and then falls. This result highlights the fact that the effect of corporate tax payments in firm value is even more complex than previously considered.
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.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.029 | 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 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".