Les effets à long terme des fonds de pension
Bibliographic record
Abstract
Cet article étudie les conséquences macroéconomiques de la détention d’une part importante du capital de l’économie par des fonds de pension. Nous supposons que le phénomène de concentration introduit une forme de concurrence imparfaite, conduisant à une baisse des salaires et à une augmentation du rendement du capital. Notre étude montre que les fonds de pension ont tendance à réduire l’accumulation de capital à long terme, quand l’utilité de cycle de vie a peu de substituabilité. Une telle baisse de capital diminue le bien-être à long terme quand l’économie est en sous-accumulation. Même dans le cas de forte substituabilité dans les préférences des agents, dans une économie en sous-accumulation, les distorsions introduites dominent l’augmentation de l’accumulation et l’utilité des agents est diminuée.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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; both teacher heads agree on what is shown here.
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".