Credit risk and the business cycle: What do we know?

Georgios Chortareas, Georgios Magkonis and Kalliopi-Maria Zekente

International Review of Financial Analysis, 2020, vol. 67, issue C

Abstract: We perform a meta-regression analysis to characterize the relationship between ex post credit risk, measured through non-performing loans and real GDP growth. Although the prior empirical literature reveals a statistically significant inverse association, the precise effect of growth performance to credit quality diverges and remains subject to several qualifications. Using estimates from 56 studies and applying a Bayesian meta-regression analysis we explore the systematic patterns of the heterogeneity in the reported estimates. According to our evidence, the specification form as well as features related to the type of data, and the sample period are factors that systematically influence the estimated results.

Keywords: Non-performing loans; Credit risk; Macro-stress testing; Business cycles; Meta-analysis (search for similar items in EconPapers)
JEL-codes: C83 E44 G21 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1057521918307579
Full text for ScienceDirect subscribers only

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:eee:finana:v:67:y:2020:i:c:s1057521918307579

DOI: 10.1016/j.irfa.2019.101421

Access Statistics for this article

International Review of Financial Analysis is currently edited by B.M. Lucey

More articles in International Review of Financial Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().