JOURNAL ARTICLE
Cross-Subsidization of Bad Credit in a Lending Crisis.
Published In: Review of Financial Studies, 2025, v. 38, n. 5. P. 1464 1 of 3
Database: Business Source Ultimate 2 of 3
Authored By: Artavanis, Nikolaos; Lee, Brian Jonghwan; Panageas, Stavros; Tsoutsoura, Margarita 3 of 3
Abstract
This article examines the corporate loan pricing behavior of a major systemic Greek bank during the Greek financial crisis, leveraging a unique dataset that includes both the actual interest rates charged and the break-even (BE) rates—defined as the marginal cost of each loan computed by the bank’s pricing model. The study finds that safer borrowers with low BE rates are charged significant positive markups, while riskier borrowers with high BE rates often face smaller or even negative markups, indicating a deliberate cross-subsidization of weaker firms by stronger ones. This pattern is explained through a dynamic theoretical model incorporating depressed collateral values, limited bank access to capital markets, and limit pricing, which predicts imperfect and asymmetric pass-through of marginal costs to loan rates during a crisis. Empirically, the pass-through from BE to actual rates is less than one, varies with the severity of the crisis, and is stronger for safer borrowers, while loans priced below BE rates require internal approval, underscoring the regulatory framework’s role in enhancing pricing transparency. The findings contribute to understanding credit market distortions in financial crises and the interplay between regulatory reforms and bank lending behavior.
Additional Information
- Source:Review of Financial Studies. 2025/05, Vol. 38, Issue 5, p1464
- Document Type:Article
- Subject Area:Politics and Government
- Publication Date:2025
- ISSN:0893-9454
- DOI:10.1093/rfs/hhae074
- Accession Number:185321459
- Copyright Statement:Copyright of Review of Financial Studies is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Looking to go deeper into this topic? Look for more articles on EBSCOhost.