Labor supply dynamics, unemployment and experience in the labor market
Bibliographic record
Abstract
Summary In the last decades, OECD labor markets faced important labor supply changes with the arrival of women and the cohorts of the baby-boom. Using a survey where workers declare their true employment experience, this paper argues that these supply trends imply more inexperienced workers. It then investigates the consequences of this fact on the skill composition of the labor force, between-groups wage inequality and the level of unemployment. The main result is that a labor market with wage rigidities may not recover from such a temporary labor supply shock: with a younger and less experienced labor force, there is higher unemployment among low-experience workers, they do not accumulate enough on-the-job human capital, this reduces in the long-run the supply of skilled (experienced) workers and the demand for unskilled workers. This intertemporal multiplication of supply shocks generates multiple equilibria, and the rigid economy is stuck to the bad equilibrium even after the shock. In a competitive labor market, in contrast, wage inequality and notably, the wage return to experience becomes higher but there is no persistence of the supply shock.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".