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.
Original language | English |
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Article number | 101421 |
Number of pages | 10 |
Journal | International Review of Financial Analysis |
Volume | 67 |
Early online date | 18 Nov 2019 |
DOIs | |
Publication status | Published - 1 Jan 2020 |
Keywords
- Non-performing loans
- Credit risk
- Macro-stress testing
- Business cycles
- Meta-analysis
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Dataset for 'Credit risk and the business cycle: what do we know?'.
Chortareas, G. (Creator), Magkonis, G. (Creator) & Zekente, K. (Creator), University of Portsmouth, 10 Feb 2020
DOI: 10.17029/b23d318f-b6d4-4cb3-ade4-3e5d90e7182a
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