(Un)Conventional monetary policy and bank risk-taking: A nonlinear relationship

Sophie Brana, Alexandra Campmas and Ion Lapteacru ()

Economic Modelling, 2019, vol. 81, issue C, 576-593

Abstract: This paper investigates the effect of monetary policy - especially unconventional monetary policy - on bank risk-taking behavior in Europe over the period 2000–2015. Using a dynamic panel model with a threshold effect, we estimate this effect on two measures of bank risk: the Distance to Default, which reflects the market perception of risk, and the asymmetric Z-score, which corresponds to an accounting-based measure of the risk. We find that loosening monetary policy (via low interest rates and increasing central banks' liquidity) has a harmful effect on banks’ risk, confirming the existence of the risk-taking channel. Moreover, we show that this relationship is nonlinear, i.e., with the sustainable implementation of unconventional monetary policies, the effects are stronger below a certain threshold.

Keywords: Risk-taking channel; Monetary policy; Asymmetric Z-score; Distance to Default; Shadow interest rate; Panel threshold model (search for similar items in EconPapers)
JEL-codes: E4 E5 G21 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0264999317315213
Full text for ScienceDirect subscribers only

Related works:
Working Paper: (Un)Conventional monetary policy and bank risk-taking: A nonlinear relationship (2019)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:ecmode:v:81:y:2019:i:c:p:576-593

DOI: 10.1016/j.econmod.2018.07.005

Access Statistics for this article

Economic Modelling is currently edited by S. Hall and P. Pauly

More articles in Economic Modelling from Elsevier
Bibliographic data for series maintained by Catherine Liu ().