Bibliographic record
Abstract
In the interbank market for overnight loans, banks sometimes trade below the central bank's deposit rate. This act is puzzling, as it seems to miss exploiting opportunities for arbitrage. In particular, why do banks lend to other banks, exposing themselves to counterparty risk, when they could earn a higher rate by depositing the balances at a risk-free central bank? This paper provides a theory to explain this anomaly. In the presence of market frictions, banks are motivated to build long-term relationships with each other to save the costs of searching for new partners every day. In this setting, lenders may sometimes cut the lending rate in the short run to keep their long-term relationship going. This relationship premium helps explain why some banks trade below the central bank's deposit rate, especially when they have a lot of liquidity. The model also helps us understand how monetary policy affects the network structure of the interbank market and the way this market functions. In a recently published updated version of this paper, we use a calibrated version of the model to study interbank trades in the Euro area.
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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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.012 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.021 | 0.002 |
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".