Real-time signals anticipating credit booms in Euro Area countries

Francesco Lucidi

No 189, Working Papers in Public Economics from Department of Economics and Law, Sapienza University of Roma

Abstract: This paper identifies credit booms in 11 Euro Area countries by tracking private loans from the banking sector. The events are associated with both financial crises and specific macro fluctuations, but the standard identification through threshold methods does not allow to catch credit booms in real time data. Thus, an early warning model is employed to predict the explosive dynamics of credit through several macro-financial indicators. The model catches a large part of the in-sample events and signals correctly both the global financial crisis and the sovereign debt crisis in an out-of-sample setting by issuing signals in real-time data. Moreover, while tranquil booms are driven by global dynamics, crisis-booms are related to the resilience of domestic banking systems to adverse financial shocks. The results suggest an ex-ante policy intervention can avoid dangerous credit booms by focusing on the solvency of the domestic banking system and financial market's overheating.

Keywords: Credit Boom; Euro Area; Early Warning; Multivariate Logit (search for similar items in EconPapers)
JEL-codes: C32 E32 E51 G01 (search for similar items in EconPapers)
Pages: 37
Date: 2019-10
New Economics Papers: this item is included in nep-eec, nep-fdg and nep-mac
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.dipecodir.it/wpsap/data/wp189.pdf (application/pdf)

Related works:
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:sap:wpaper:wp189

Access Statistics for this paper

More papers in Working Papers in Public Economics from Department of Economics and Law, Sapienza University of Roma
Bibliographic data for series maintained by Luisa Giuriato ().