An Analysis of Effective Marginal Tax Rates in Quebec
Bibliographic record
Abstract
This article draws a portrait of effective marginal tax rates (EMTRs) on labour income in Quebec. It aims to improve the understanding of the impact of tax policy on the behaviour of economic agents. Using an accounting microsimulation model that reproduces the system of taxes and transfers in 2002 in Quebec, we measure the EMTRs that result from the interaction of the mechanisms of income taxation and redistribution. Moreover, we evaluate the distribution of EMTRs in the population. The analysis of EMTRs shows, inter alia, that family policy, whose assistance is targeted toward low-income families, generates high levels of EMTRs ascribable to the generally fast reduction of transfers as income increases. More than a quarter of heads of single-parent households face an EMTR that can reach, and even exceed, 80 percent. As for two-parent families, they mostly face EMTRs of around 50 percent. We show the importance of accounting for EMTR heterogeneity, both with respect to types of families and levels of incomes, as well as evaluating the variability of EMTRs in the population.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".