Cohort patterns in Canadian earnings: assessing the role of skill premia in inequality trends
Bibliographic record
Abstract
In this paper we document the pattern of change in age‐earnings profiles across cohorts and evaluate its implications. Using synthetic cohorts from the survey of Consumer Finances over the period 1971 to 1993, wwe show that the age‐earnings profiles of Canadian men have been deteriorating for more recentcohorts in comparison with older cohorts. We find this pattern for both high school and university educated workers. In no case do we find evidence that the return to gaining experience has been increasing over time, nor do we find increased within‐cohort dispersion of earnings. We view these findings as conflicting with the hypothesis that increased skill premia largely explain the observed increase in dispersion of male weekly earnings. JEL Classification: J31, O33 Ce mémoire documente le pattern de changements dans les relations âges‐gains d'une cohorte à l'autre, et en analyse les implications. Utilisant des cohortes synthétiques pour la période 1971–93, on montre que les profils âges‐gains des hommes au Canada se sont détériorés dans les cohortes les plus récentes. On ne trouve pas de résultats qui montreraient que le rendement sur l'expérience accumulée s'est accru dans le temps ou qu'il y a dispersion accrue des gains à l'intérieur des cohortes. Les auteurs suggèrent que ces résultats contredisent l'hypothèse que des primes accrues pour les habiletés expliqueraient l'accroissement qu'on a observé dans la dispersion des gains des hommes au Canada.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".