Exporting, demand for skills and skill mismatch: Evidence from employers' hiring practices
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract We exploit information from a classification of occupations to identify separately formal qualification requirements linked to a job and formal qualifications of a worker who filled the job for the universe of firms in Slovenia. We find that exporters were more likely to hire over‐qualified workers than they did prior to becoming exporters even though they did not change the qualification requirements of their vacancies. Firms were more likely to demand other skills (leadership, knowledge of foreign languages) once they began to export. These findings suggest that skill upgrading by exporters reflects differences in terms of skill demand as well as the way workers match to jobs. This distinction is blurred in existing studies on skill upgrading by exporters because these studies rely solely on the information about the qualifications of hired workers. Our findings are consistent with a framework in which firms become more productive and offer higher wages once they start to export, workers' qualifications and firms' productivity are complementary inputs, and search is costly.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it