Immigrants’ net direct fiscal contribution: How does it change over their lifetime?
Bibliographic record
Abstract
Abstract Life‐cycle direct public fiscal contributions and transfers are studied using longitudinal income tax data from 1982 to 2016 and administrative files for immigrants landed in Canada from 1980 to 2016. Relative to a comparison group comprising the Canadian‐born and immigrants landed before 1980, immigrants since 1980 have a lower average net direct fiscal contribution (NDFC) during their working years due to their lower taxes and social security contributions but a higher average NDFC after 65 years of age because of reduced public pension eligibility and entitlement. Immigrants who landed at younger than 19 years old have much higher direct fiscal contributions than other age‐at‐arrival groups and reach their peak of contributions around 10 years earlier in life than other age‐at‐arrival groups. Immigrants whose age at arrival is above 65 have a less negative average NDFC than other age‐at‐arrival groups over the above‐65 life cycle. These life‐cycle age𠄁at‐arrival trajectories are stable for immigrants in different landing cohorts. We apply the life‐cycle estimates to project the present discounted value of lifetime NDFCs for immigrants who landed in 2016. For each landing age group, refugees and family class immigrants have negative or zero average present values of life‐cycle NDFCs, much below that of economic immigrants.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".