Conjecture sur le comportement de l’impôt sur le revenu des particuliers
Bibliographic record
Abstract
This fiscal essay tries to specify the economic variables which have an effect upon the personal income tax during a business cycle. After clearing out the concept of trend elasticity and cyclical elasticity, we propose a model based on the concept of elasticity which will permit us to see the income increases due to the overall increase in employment (or a decrease in the rate of unemployment), and those produced by the global increase in wealth (such as the increase in per capita revenue due to productivity, inflation and so on). Then we apply this model to the federal personal income tax collected in Quebec for ten income classes and we find that there is a difference between the average taxation rate due to the increment of employment and the average taxation rate due to wealth increase and consequently at the elasticity level also. However, the difference is not statistically significant. So, our theoretical model and its application explains partly why the income elasticity of the personal income tax appears to be greater in periods of decline in economic activity and tends to abate fairly sharply as expansionary momentum is restored.
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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 | 0.003 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".