Changes over time in union relative wage effects in the UK and the US revisited
Bibliographic record
Abstract
This paper examines the impact of trade unions in the US and the UK and elsewhere.In both the US and the UK, despite declining membership numbers, unions are able to raise wages substantially over the equivalent non-union wage.Unions in other countries, such as Australia, Austria, Brazil, Canada, Chile, Cyprus, Denmark, Japan, New Zealand, Norway, Portugal and Spain, are also able to raise wages by significant amounts.In countries where union wage settlements frequently spill over into the non-union sector (e.g.France, Germany, Italy, the Netherlands and Sweden) there is no significant union wage differential.The estimates from the seventeen countries we examined averages out at 12 per cent.Time series evidence from both the US and the UK suggests three interesting findings.First, the union differential in the US is higher on average than that found in the UK (18 per cent compared with 10 per cent).Second, the union wage premium in both countries was untrended in the years up to the mid-1990s.Third, in both countries the wage premium has fallen in the boom years since 1994/95.It is too early to tell whether the onset of a downturn in 2002 will cause the differential to rise again or whether there is a trend change in the impact of unions.It is our view that most likely what has happened is that the tightening of the labor market has resulted in a temporary decline in the size of the union wage premium.Time will tell whether the current loosening of the labor market, that is occurring in both countries, will return the union wage premium to its long run values of 10 per cent in the case of the UK and 18 per cent in the case of the US.On the basis of past experience it seems likely that they will.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".