The Pivotal Role of Capital Gains in Efficient and Progressive Tax Reform
Bibliographic record
Abstract
Increased, targeted taxation of capital gains is key to making the personal income tax more progressive, and it can also contribute to a more efficient system. This article assesses a two-tier capital gains tax that would apply a second, higher inclusion rate for gains above a specified threshold. Relative to a general increase in the inclusion rate—widely promoted by tax analysts—a two-tier scheme would focus on high-income, high-wealth taxpayers, forgo limited revenue, and be more publicly acceptable and politically viable. Relative to reforms to the alternative minimum tax (AMT), the two-tier scheme would be simpler, cover more taxpayers, capture more revenue, and conform more closely to the notion that "the rich pay their fair share." The article explains how capital gains are an amalgam of capital and labour inputs, often containing supernormal returns that are an efficient target for increased taxation. The article further details the high concentration of recurrent large capital gains at top income levels and critically assesses arguments commonly made against raising the gains inclusion rate. It also identifies desirable companion measures for a two-tier gains tax—including restoration of income averaging and abolition of the federal 33 percent top tax bracket and the AMT itself. In short, the current 50 percent capital gains deduction serves as a gateway for endless tax-minimizing and economy-distorting stratagems. Closing that gate even partway for those most prone to enter into such planning would be pivotal in making Canada's tax system both more efficient and more progressive.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.016 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".