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| Format: | Preprint |
| Veröffentlicht: |
2025
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| Online-Zugang: | https://arxiv.org/abs/2512.21553 |
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| _version_ | 1866914220309741568 |
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| author | Qu, Chunyu |
| author_facet | Qu, Chunyu |
| contents | This article examines how legacy lending relationships shape the allocation of emergency credit under severe information frictions. Using a novel dataset linking Small Business Administration (SBA) loan records with Dun and Bradstreet microdata for over 26 million U.S. firms, I investigate whether prior participation in the SBA 7(a) program acted as a gateway to the Paycheck Protection Program (PPP). Employing entropy balancing to construct a strictly comparable counterfactual group, I document a distinct dynamic evolution in credit rationing. In the program's initial "panic phase" in April 2020, banks relied heavily on legacy ties as a screening technology: firms with prior 7(a) relationships were approximately 29 percentage points more likely to receive funding than observationally identical non-7(a) firms. By June 2021, however, this insider advantage had largely vanished, suggesting that policy adjustments and extended timelines eventually mitigated the initial intermediation frictions. These findings highlight a fundamental trade-off between speed and equity in crisis response. While leveraging existing credit rails accelerates deployment, it systematically excludes informationally opaque borrowers. I discuss policy implications for designing future digital infrastructure to decouple verification from historical lending relationships. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_21553 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Legacy Lending Relationships and Credit Rationing: Evidence from the Paycheck Protection Program Qu, Chunyu General Economics Economics This article examines how legacy lending relationships shape the allocation of emergency credit under severe information frictions. Using a novel dataset linking Small Business Administration (SBA) loan records with Dun and Bradstreet microdata for over 26 million U.S. firms, I investigate whether prior participation in the SBA 7(a) program acted as a gateway to the Paycheck Protection Program (PPP). Employing entropy balancing to construct a strictly comparable counterfactual group, I document a distinct dynamic evolution in credit rationing. In the program's initial "panic phase" in April 2020, banks relied heavily on legacy ties as a screening technology: firms with prior 7(a) relationships were approximately 29 percentage points more likely to receive funding than observationally identical non-7(a) firms. By June 2021, however, this insider advantage had largely vanished, suggesting that policy adjustments and extended timelines eventually mitigated the initial intermediation frictions. These findings highlight a fundamental trade-off between speed and equity in crisis response. While leveraging existing credit rails accelerates deployment, it systematically excludes informationally opaque borrowers. I discuss policy implications for designing future digital infrastructure to decouple verification from historical lending relationships. |
| title | Legacy Lending Relationships and Credit Rationing: Evidence from the Paycheck Protection Program |
| topic | General Economics Economics |
| url | https://arxiv.org/abs/2512.21553 |