Explaining and forecasting bank loans. Good times and crisis
Grégory Levieuge
Working papers from Banque de France
Abstract:
This paper aims to develop a parsimonious model to explain and forecast bank loans to non-financial companies during calm periods as well as in situations of financial turmoil. In doing so, we are led to gauge the marginal informational content of simple leading indicators, and to investigate potential non-linearity in credit dynamics. This framework is applied to the French context, over a period including financial, banking and sovereign debt crises. In accordance with firms and banks balance sheets effects, the growth rate of equity prices appears to be one of the most interesting leading indicator as well as a significant threshold variable for explaining regime switching. However, our results highlight the difficulties to accurately predict the right credit dynamics regimes. A simple VAR model finally performs better.
Keywords: Credit; Forecast; VECM; Threshold VAR; leading indicators. (search for similar items in EconPapers)
JEL-codes: C22 E47 E51 (search for similar items in EconPapers)
Pages: 47 pages
Date: 2015
New Economics Papers: this item is included in nep-for and nep-mac
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
https://publications.banque-france.fr/sites/defaul ... g-paper_566_2015.pdf (application/pdf)
Related works:
Journal Article: Explaining and forecasting bank loans. Good times and crisis (2017) 
Working Paper: Explaining and forecasting bank loans. Good times and crisis (2017)
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:bfr:banfra:566
Access Statistics for this paper
More papers in Working papers from Banque de France Banque de France 31 Rue Croix des Petits Champs LABOLOG - 49-1404 75049 PARIS. Contact information at EDIRC.
Bibliographic data for series maintained by Michael brassart ().