The deductibility of provincial business taxes in a federation with vertical fiscal externalities
Bibliographic record
Abstract
Should provincial business taxes be deductible under a federal profit tax? We show that the ‘optimal deductible,’ which neutralizes the vertical fiscal externality between the federal and provincial government, is the change in the federal tax base per dollar of tax revenue collected by the provincial government. The optimal payroll tax deductibility rate depends on the extent to which it is shifted to workers and on the difference between the federal tax rates on profits and on labour income. Two apparently contradictory positions – full deductibility of a payroll tax and non‐deductibility – are special cases of our model. La déductibilité des taxes provinciales imposées aux entreprises dans une fédération où il y a des externalités fiscales verticales. Est‐ce que les taxes provinciales imposées aux entreprises devraient être déductibles de l'impôt fédéral sur les profits? Les auteurs montrent que l'optimum de déductibilité qui neutralise les externalités fiscales verticales entre le fédéral et les provinces est le changement dans la base d'imposition fédérale par dollar de revenu fiscal collecté par le gouvernement provincial. Le taux de déductibilité optimal d'un impôt sur les salaires dépend de la portion du fardeau fiscal qui est déportée vers les travailleurs et de la différence entre les taux d'imposition du fédéral sur les profits et sur le revenu du travail. Deux positions apparemment contradictoires – pleine déductibilité d'un impôt sur les salaires et déductibilité nulle – sont des cas spéciaux du modèle général.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".