Financial Constraints and the Incentive for Tax Planning
Bibliographic record
Abstract
In this study, we investigate the association between financial constraints, at both the macroeconomic and firm-specific level, and one potentially significant source of internal funds available to firms – cash savings generated through tax planning. In equilibrium a firm will undertake tax avoidance strategies if the marginal benefit (i.e., reduction in taxes payable) exceeds the marginal costs. Assuming the cost of implementing tax avoidance strategies does not increase for financially constrained firms, this suggests that firms will increase tax avoidance as access to external funds becomes more costly. Measuring financial constraints based on both macroeconomic measures (change in GDP and bank lending tightening) and firm-specific measures (a financial distress indicator based on the Altman Z-score and the decile ranking of the Whited and Wu 2006 financial constraint index), we find that firms facing financial constraints exhibit lower cash effective tax rates. Understanding how financial constraints affect tax avoidance and the interplay between macroeconomic forces and firm-level tax avoidance behavior is important as legislators look for ways to reduce the federal deficit.
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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 | 0.012 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".