Distributional effects of social security reforms: The case of France
Bibliographic record
Abstract
Abstract This paper assesses the impact of two social security reforms using a calibrated, dynamic life cycle model. It quantifies the long‐run distributional impact of two sets of reforms in France: (1) the 2013 reform of Prime Minister Ayrault, which modified the parameters of a defined benefit (DB) plan, and (2) a hypothetical reform that changes the system to a notional defined contribution (NDC) plan, similar to that in Italy. First, on aggregate welfare, the Ayrault reform and the hypothetical switch to NDC yield contrasting results. The Ayrault reform improves aggregate welfare, which is not the case for the NDC reform. Welfare comparisons are made with respect to the “benchmark economy,” where increases in life expectancy occur and are dealt with only through a higher contribution rate. Second, both reforms yield unequal distributions of welfare changes, with low‐skill workers on the losing end. Under the Ayrault reform, low‐skill workers delay retirement by two years, to age 62. Under NDC reform, pensions for low‐skill workers fall substantially as inequalities during the work life translate directly into inequalities in pensions. The switch to an NDC scheme leads to a more unequal society in terms of asset and welfare distribution.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".