Skills heterogeneity among graduate workers: real and apparent overeducation in the Spanish labor market
Bibliographic record
Abstract
This paper relaxes the assumption of homogeneous skills among graduate workers and proposes a new approach to differentiate between real and apparent overeducation based on the level of cognitive skills actually achieved by the individuals. This proposal is applied to the study of the wage effects of overeducation in the Spanish labor market using data from PIAAC. The results suggest that between a quarter and a half of the graduate workers who appear to be overeducated in the Spanish labor market could be considered as being only apparently overeducated since they show a lower level of skills than that corresponding to their educational level or, alternatively, a level of cognitive skills which is commensurate with their job. Different returns are found for each group of overeducated individuals both when compared with adequately educated peers within a similar level of education (with greater wage penalties for apparently overeducated workers) and when the comparison is done with well-matched co-workers doing a similar job (with a wage premium for real overeducation but no significant returns for apparently overeducated workers). These results point to the need of taking account of skills heterogeneity within an educational level when returns to overeducation are analyzed.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".