The Erosion Effects of Income Taxes and Inflation on GIC Investment Returns
Bibliographic record
Abstract
This report develops an algorithm which is used to compute the real (afterinflation) and after-tax returns (RATs) on Guaranteed Investment Certificates (GICs) during the period 1974 to 2003. For our analysis, we assume these products were periodically rolled-over into identical term instruments at the (historical) rates quoted by the major banks and trust companies at the beginning of the year. Our main finding is that annualized RAT returns have been negative for Ontario investors in the top marginal tax rate for a majority of the investigated time period. Even when positive, RATs rarely exceeded one percent during most years. More precisely, any Canadian investor whose marginal tax rate exceeded 35.5% earned, on average, a negative RAT return from 1-year GICs which were continuously rolled over during the last 30 years. And, for longer maturity 3-year and 5-year GICs – for which the quoted interest rates are typically greater -- the breakeven tax rate was only slightly higher. We conclude by arguing that for many Canadians, the strategy of rolling over so-called riskfree GICs outside of a tax shelter is a sure way to destroy long-term wealth.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".