Disasters and lending signals: From borrower information to community characteristics

Winta Beyene

No 455, SAFE Working Paper Series from Leibniz Institute for Financial Research SAFE

Abstract: I study the informational value of community resilience in credit markets during natural disasters. Exploiting a severe flood in Germany in 2013, I combine loan-level data on car loans with a composite measure of community resilience based on structural local characteristics linked to disaster recovery capacity. After the flood, only low-income borrowers faced credit tightening, but in high-resilience areas they experienced smaller rate hikes and maintained access to credit. Resilience also predicts repayment after disasters, yet banks ignore it in normal times. This state-contingent reliance shows that community resilience enters credit pricing only in crises, when its information content beyond standard borrower characteristics is valuable enough to justify adoption.

Keywords: Financial resilience; natural disasters; social capital; consumer credit (search for similar items in EconPapers)
Date: 2025
New Economics Papers: this item is included in nep-inv and nep-mfd
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:safewp:325484

DOI: 10.2139/ssrn.5435455

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