US Bank Lending to Small Businesses: An Analysis of COVID-19 and the Paycheck Protection Program
Bibliographic record
Abstract
This paper examines the characteristics of banks and their lending behavior in relation to Paycheck Protection Program (PPP) loans and commercial and industrial (C&I) loans to small businesses during the COVID-19 pandemic. Our findings show that lenders facing greater risk tended to lend more PPP loans, consistent with the risk-aversion theory. Specifically, banks with a higher loan–deposit ratio, lower overall profitability, poorer loan quality, and higher exposure to risks in business (C&I) loans are characterized by higher PPP loans. C&I loans to all businesses are negatively related to the loan–deposit ratio and loan loss allowance ratio, but are positively linked with the capital ratio. However, we find important differences in C&I lending to small businesses versus large businesses. Furthermore, there is evidence regarding the success of targeting PPP loans towards more productive sectors of the US economy. Using FDIC-defined banks’ lending specializations, we show that banks focused on international lending had a limited role in PPP lending.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".