Bibliographic record
Abstract
Theory predicts that there is a close link between bank credit supply and the evolution of the business cycle.Yet fluctuations in bank-loan supply have been hard to quantify in the time-series.While loan issuance falls in recessions, it is not clear if this is due to demand or supply.We address this question by studying firms' substitution between bank debt and non-bank debt (public bonds) using firm-level data.Any firm that raises new debt must have a positive demand for external funds.Conditional on issuance of new debt, we interpret firm's switching from loans to bonds as a contraction in bank credit supply.We find strong evidence of substitution from loans to bonds at times characterized by tight lending standards, high levels of non-performing loans and loan allowances, low bank share prices and tight monetary policy.The bank-to-bond substitution can only be measured for firms with access to bond markets.However, we show that this substitution behavior has strong predictive power for bank borrowing and investments by small, out-of-sample firms.We consider and reject several alternative explanations of our findings.
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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 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".