Does Increasing Contribution Length Lead to Higher Retirement Age? Evidence from the 1993 French Pension Reform,” mimeo
Bibliographic record
Abstract
This paper offers the first ex post evaluation of the incentive effects of the 1993 French pension reform. This private sector reform was meant both to reduce replacement rates and to increase retirement age. In order to induce later retirement, the gov-ernment increased the number of quarters of contribution necessary to obtain a full rate pension from 150 to 160 quarters. We use both the Echantillon Interrégime des Retraités (EIR 2001) and the exhaustive administrative data from the CNAV (1994-2003) in order to estimate the elasticity of retirement age to the length of contribution necessary to obtain the full rate. We take advantage of the fact that different groups were affected differently by the reform (depending both on birth year and contribu-tion length at age 60) in order to identify precisely the behavioral impact of changing incentives, using a difference-in-difference approach. We find that one additional quarter of necessary contribution led to an average increase of 2 months in retire-ment age, corresponding to an elasticity of 0.7. This fairly high response of French workers should be put in perspective with the high level of penalty associated with
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".