Identifying credit supply shocks with bank-firm data: Methods and applications

By Hans Degryse, Olivier De Jonghe, Sanja Jakovljević, Klaas Mulier, G. Schepens. Journal of Financial Intermediation, 2018

207 citations recorded by the source corpus.

Current empirical methods to identify and assess the impact of bank credit supply shocks rely strictly on multi-bank firms and ignore firms borrowing from only one bank. Yet, these single-bank firms are often the majority of firms in an economy and most prone to credit supply shocks. We propose and underpin an alternative demand control (using industry-location-size-time fixed effects) that allows identifying timevarying cross-sectional bank credit supply shocks using both single- and multi-bank firms. Using matched bank-firm credit data from Belgium, we show that firms borrowing from banks with negative credit supply shocks exhibit lower financial debt growth, asset growth, investments, and operating margin growth. Positive credit supply shocks are associated with bank risk-taking behaviour at the extensive margin. Importantly, to capture these effects it is crucial to include the single-bank firms when identifying the bank credit supply shocks.

Subfields: Accounting, Finance

View Paper: https://www.semanticscholar.org/paper/deeb1e6d3fd0cb696f50d9799451007d807cda40

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Citations in the corpus

Some Borrowers Are More Equal than Others: Bank Funding Shocks and Credit Reallocation* (2019, methodology): “A similar approach is used by Edgerton (2012), Degryse et al. (2018) and Morais et al. (2018).”
Is there a zero lower bound? The effects of negative policy rates on banks and firms (2019, unknown): “The result is robust as we saturate the equation with an increasing number of fixed effects, 16 Degryse et al (2019) suggest that this methodology works at least as well as widely used methodologies identifying supply only from firms with multiple banks relationships.”