Labor Market Behavior Differences between the Young and Old in a Search Theoretical Model
Bibliographic record
Abstract
This paper studies the labor market behavior differences across different age groups in Canada. I use data from 2000 to 2024, which includes the Great Recession and the Covid-19 recession, to conduct analysis. The data show that compared to the older workers, young workers not only have a much higher unemployment rate, but also a higher job finding rate and job separation rate. The volatilities in the unemployment and separation rates for the young workers are also much higher than those for the older workers. I then use a labor search model to study the differences. I calibrate the model to the Canadian data and simulate the model assuming the economy is subject to a productivity shock. I find that there are significant labor market differences between young workers and older workers: In particular, the response in the unemployment rate of the young workers to the shock is much more pronounced compared to the older age groups. I also find that the labor market differences between young and old workers are mainly caused by the differences in the job finding rate.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".