Tax Setting in a Federal System: The Case of Personal Income Taxation in Canada ∗
Bibliographic record
Abstract
In a decentralised tax system, the effects of tax policies enacted by one government are not confined to its own jurisdiction. First, if both the regional and the federal levels of government co-occupy the same fields of taxation, tax rate increases by one layer of government will reduce taxes collected by the other. Second, if the tax base is mobile, tax rate increases by one regional government will raise the amount of taxes collected by other regional governments. These sources of fiscal interdependence are called in the literature vertical and horizontal tax externalities, respectively. Third, as Smart (1998) shows, if equalisation transfers are present, an increase in the standard equalisation tax rate provides incentives to raise taxes to the receiving provinces. A way to check the empirical relevance of these hypotheses is to test for the existence of interactions between the regional tax rate, on the one hand, and the federal tax rate, the tax rate set by competing regions, and the standard equalisation tax rate, on the other hand. Following this approach, this paper estimates provincial tax setting functions with data on Canadian personal income taxation for the period 1982‐1996. We find a significant positive response of provincial tax rates to changes in the federal income tax rate, the tax rates of competing provinces, and the standard equalisation rate (only for receiving provinces). We also find that the reaction to horizontal competition is stronger in the provinces that do not receive equalisation transfers.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".