Bibliographic record
Abstract
We analyse the coordination problem in the labour market by endogenizing the matching function and the wage share. Each firm posts a wage to maximize the expected profit, anticipating how the wage affects the expected number of applicants. In equilibrium workers apply to firms with mixed strategies, which generate coordination failure and persistent unemployment. We show how the wage share, unemployment, and the welfare loss from the coordination failure depend on the market tightness and the market size. The welfare loss from the coordination failure is as high as 7.5 per cent of potential output. JEL Classification: C78, J64 Les auteurs analysent le problème de la coordination dans le marché du travail en endogénéisant la fonction 'arrimage et la part des revenus qui va aux salaires. Chaque entreprise définit le niveau de salaire qui maximise ses profits anticipés, en tenant compte de l'effet de ce niveau de salaire sur le nombre des applications qu'elle peut anticiper. De même, les travailleurs font application auprès d'une entreprise à un salaire donné en tenant compte d'une certaine relation d'équivalence entre niveau de salaire et probabilité d'obtenir l'emploi. Voilà qui engendre incoordination et chômage persistant. On montre que la part des revenus qui revient aux salaires, le niveau de chômage, et les pertes de bien‐être attribuables au manque de coordination dépendent de la taille du marché et du degré de rareté de la main d'oeuvre. Les pertes de bien‐être attribuables au manque de coordination correspondent à quelques 7,5 pour‐cent de la production potentielle.
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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 | 0.009 |
| 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 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".