Monetary Policy Transmission to Small Business Loan Performance: Evidence from Loan-Level Data
Bibliographic record
Abstract
This paper analyzes the dynamic and heterogeneous responses of loan performance to a monetary-policy shock using loan-level panel data for small-scale private firms in Canada. Our dataset contains detailed loan characteristics information that allows us to distinguish the effects of the aggregate-demand channel, which affects loan performance through general-equilibrium effects, and the cash-flow channel that directly impacts debt service of firms through variable rates. We find that the effects on loan performance through both channels materialize with a delay and are persistent over time. The peak effect of the cash-flow channel is as large as that of the aggregate-demand channel. Moreover, we investigate whether collateral can reduce the sensitivity of variable-rate loan performance to a policy-rate shock through an ex post disciplinary effect that incentivizes loan repayment by small firms. We find that collateral induces repayment incentives of borrowers relative to unsecured loans but only for ex ante safe loans that are used for investment rather than for other purposes such as working capital. This implies that collateral has a limited impact on reducing financial frictions of small firms.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".