Une analyse économétrique du comportement d’intermédiation financière des sociétés de crédit populaire : le cas des caisses populaires
Bibliographic record
Abstract
Considering the Caisses populaires as a financial system, we propose an econometric model of its consolidated balance sheet built around the following four major blocks. The first one presents a dynamic sub-model of the Caisses' asset portfolio, which emphasizes their intermediation among assets on the basis of the latter interest rates. In a second block, these rates are endogenized with respect to the key variables of both the real and monetary sectors of the economy. On the liability side, the Caisses' deposit market is dealt with in a third block, namely a demand for deposits or flow equation and a supply of deposits or rate setting operation. Finally, adjustment equations for the balance sheet items not already considered, are grouped in a fourth block. The overall model is dynamized through the deposit equation. From the model's econometric estimation, we arrive at the following conclusions about financial management and liquidity policies. On the asset side of the balance sheet, the Caisses aim mainly at satisfying their members' needs for mortgages and, to a lesser but growing degree, for consumer loans. Next, for the funds remaining after satisfying internal needs, the institution proceeds to some sort of secondary, medium-term intermediation, then preferring quasi-liquid and higher yielding bonds to reserves. On the liability side, the Caisses seem to set their rate on deposits on the basis of the one for chartered banks (price leadership) as well as on the basis of the most representative asset rates, i.e. the ones on consumer and mortgage loans. Finally, the public demand for the Caisses' deposits, is more a function of the borrowing privileges offered to the members than of the intrinsic competitive rate paid on them.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".