Immigration et impact fiscal net : une analyse de cycle de vie par la microsimulation de l'impact fiscal net des immigrants au Canada
Bibliographic record
Abstract
L’accroissement de la population vieillissante au Canada pose un défi majeur pour la viabilité des programmes de sécurité sociale. Avec une pyramide d'âge inversée, une part croissante de la population consomme davantage de services publics tout en étant économiquement inactive. Le système de protection sociale canadien fait face à des pressions fiscales considérables. Les nouveaux immigrants, généralement plus jeunes que la population native, peuvent tempérer la hausse du ratio de dépendance. Cependant, l'intégration économique des immigrants, influencée par des barrières linguistiques et la reconnaissance des qualifications, reste un enjeu crucial. Cette recherche emploie la microsimulation démographique, pour estimer l’impact fiscal de cycle de vie adulte des immigrants au Canada. Selon le modèle développé pour ce mémoire, l’impact fiscal net annuel des immigrants s’estimerait à -747$ en moyenne, comparativement à 2565$ pour les natifs, soit une différence de 3312$. Sur leur cycle de vie adulte, ces résultats correspondent à -659$ et 1286$ respectivement, soit un écart de 1945$. En analysant des scénarios alternatifs, le modèle montre que la réduction du nombre d’immigrants affecterait peu l’impact fiscal net par personne. En revanche, une meilleure intégration économique des immigrants en ciblant des politiques facilitant leur emploi et la reconnaissance de qualifications pourrait grandement augmenter l’impact fiscal net moyen des Canadiens, réduisant ainsi les pressions sur le système de protection sociale. The increasing ageing population in Canada poses a major challenge to the viability of social security programs. With an inverted age pyramid, a growing proportion of the population consumes more public services while being economically inactive. The Canadian social welfare system faces considerable fiscal pressures. New immigrants, generally younger than the native population, can temper the rise in the dependency ratio. However, the economic integration of immigrants, influenced by language barriers and the recognition of qualifications remains a crucial issue. This research employs demographic microsimulation to estimate the fiscal impact of immigrants' adult life cycles in Canada. According to the model developed for this study, the annual net fiscal impact of immigrants is estimated at -747$, compared to 2565$ for native-born individuals, a difference of 3312$. Over their adult life cycles, these results correspond to -659$ and 1286$ respectively, a gap of 1945$. The model shows that reducing the number of immigrants would have little effect on the net fiscal impact per capita. In contrast, better economic integration of immigrants, by targeting policies that facilitate their employment and recognition of qualifications, could significantly increase the average net fiscal impact of Canadians, thereby reducing pressures on the social welfare system.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".