The Economic Costs of Increased Marginal Tax Rates in Canada
Bibliographic record
Abstract
Economists often focus on marginal tax rates (the extra tax an individual (or firm) will owe to the government for engaging in a little more of the taxed activity) as particularly important for altering economic behaviour. The marginal tax rate is significant because it indicates the amount of tax a person will pay for an additional dollar earned. An extensive literature documents that taxes — particularly progressive income and capital taxes — reduce economic growth, saving and investment, business formation, and job creation.Superficially, with a top federal personal income tax rate of 29 percent, Canada appears to enjoy the lightest tax burden among the G7 countries and Australia. However, this appearance is deceptive. Canada places a relatively greater emphasis on provincial taxation than do other countries in its peer group. For example, both Quebec and Ontario have steeply progressive income tax codes, with top rates of 24 and 18.97 percent, respectively.Also, the top marginal rate kicks in at different thresholds around the world: in Canada, personal income tax thresholds are typically lower than in the other reference countries. In fact, both the federal top rate and the threshold at which that top rate kicks in are low compared to other countries. Taken together, these two adjustments put Canada’s tax rates somewhere in the middle of those in the peer countries, underscoring the need for federal and provincial tax relief and reform if Canada wishes to build on past improvements and its current success.The most obvious solution to the relatively high total burden is income tax reform, particularly at the provincial level. The principles for income tax reform are straightforward: flatten rates and broaden the tax base (by reducing or eliminating tax credits, deductions, etc.).
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 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".