Wage Mobility in Europe - A Comparative Analysis Using Restricted Multinomial Logit Regression
Bibliographic record
Abstract
In this paper, we investigate cross-country differences in wage mobility in Europe using the European Community Household Panel for the years 1994-2001. The paper is particularly focused on examining the impact of economic conditions, welfare state regimes and institutional constraints such as employment regulation, on wage mobility.. Using the pooled dataset, annual decile transitions are analyzed by applying a log-linear approach that is very much similar to a restricted multinomial logit model. Contrary to the standard probit approach – with which we also compare our results- this allows us to estimate a model that accounts for all types of associations between the variables involved and for the full range of origin states. It appears that regime type in combination with the economic conditions and the separate institutional measures indeed explains a substantial part of the cross-country variation. The findings also confirm the existence of an inverse U-shape pattern of wage mobility with increasing wages, showing a great deal of low and high-wage persistence in all countries.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".