Bibliographic record
Abstract
Since being introduced in 1972, taxable capital gains in Canada have been based on partial inclusion of nominal capital gains (i.e., the difference between sale and purchase prices). The inclusion rates have varied between 50 and 75 percent but have been 50 percent since 2000. Recently, there has been discussion of increasing capital gains taxes by increasing the inclusion rate (back to) 75 percent. In this paper, I argue that the capital gains tax is a poorly designed and inequitable tax and so, rather than make another ad hoc adjustment to the inclusion rate, a superior option is to reform capital gains taxation by indexing for inflation so as to measure real capital gains (i.e., the increase in purchasing power that is realized). The Toronto Stock Exchange Composite Index and the index of consumer prices are used to determine 40 and 50 year sequences of the differences between real and nominal measures of capital gains under both 50 and 75 percent inclusion rates for an index asset held for 20, 10 and 5 years. The work demonstrates that taxable capital gains are over and under assessed considerably relative to real capital gains. For example, over the period 1996 to 2020, differences between the taxable capital gains under a 75 percent inclusion rate and real gains would have been about 20 percent for a 10-year hold and about 33 percent for a 5 year hold. The results demonstrate the varying disparities between real gains and those under partial inclusion. Such disparities imply wide differences in effective tax rates and so inequities among investors, over time and with other taxpayers. This evidence argues persuasively that Canada’s capital gains taxation should abandon partial inclusion and turn to serious reform by indexing for inflation.
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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 | 0.004 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".