Why Larger Lenders obtain Higher Returns: Evidence from Sovereign Syndicated Loans
Bibliographic record
Abstract
Lenders that fund larger shares of a syndicated loan typically receive larger percentage upfront fees than smaller lenders. This paper studies sovereign syndicated loan contracts in the period 1982-2006 to explore this fact. In our dataset of 288 contracts large lenders obtain on average an 8.5 percent higher return on their funds than small lenders who join the syndicate. Our analysis shows that the return premium large lenders receive is positively affected by anticipated future liquidity problems of the borrower and by the number of banks. Our analysis also reveals that the return premium is not used to control the number of banks that join the syndicate. We interpret our findings as indicating that the fee structure on syndicated loans incorporates anticipated costs associated with a borrower illiquidity, notably the costs of coordinating the workout and providing liquidity insurance, but that the fee structure does not serve the additional purpose of curbing these costs by reducing the number of lenders in the syndicate.
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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 | 0.003 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".