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The global financial crisis and European sovereign debt crisis underlined the links between the banking sector and sovereign risk. This paper uses a machine learning technique (random forest regression) to examine whether sovereign ratings account for the potential spillovers from the banking sector to sovereign risk. To do so, we use a panel of sovereign ratings issued by the three main credit rating agencies (CRAs) (Fitch, S&P and Moody’s) for 30 European countries from 2002 to 2016. We find that in addition to the main economic indicators (macroeconomic, government and institutional quality factors), the soundness of the banking system is relevant in determining the sovereign rating. In fact, with the outbreak of the crisis, the importance of these banking sector characteristics (namely, liquidity, concentration and volume of non-performing loans) for sovereign ratings increased substantially. These results suggest a change in CRAs’ policies since the onset of the crisis, involving a re-appraisal of the structure of the banking sector when assessing countries’ sovereign risk.
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Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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