Breaking the Bank? A Probabilistic Assessment of Euro Area Bank Profitability

Abstract

This paper explores the determinants of profitability across large euro area banks using an approach based on conditional profitability distributions. The most reliable determinants of bank profitability are real GDP growth and the nonperforming loan (NPL) ratio. The estimated conditional distributions reveal that, while higher growth would raise profits on average, a large swath of banks would most likely continue to struggle even amid a strong economic recovery. Therefore, for some banks, a determined reduction in NPLs combined with cost efficiency improvements and customized changes to their business models appears to be the most promising strategy for durably raising profitability.

Keywords: Bank profitability; Conditional distributions; Quantile regressions.

Fig. 1

Bank Profitability: Euro Area and U.S. Banks (Median return on equity; in%). Source:IMF (2020).

Fig. 2

Euro Area Banks (“Significant Institutions”): Key Trends and Stylized Facts. Sources: Bloomberg Finance L.P., Fitch Connect, and authors’ calculations. Notes: Based on a balanced sample of 45 SSM (Single Supervisory Mechanism) banks over 2007–2016, with 56% of end-2016 SSM assets. Cost of equity estimates, ranging from 8–10%, are subject to various caveats, including with regard to measurement.

Fig. 3

Illustrative Conditional Profitability (ROE) Distributions. Source: Authors’ estimates. Note: The figure shows illustrative baseline and “shocked” conditional bank ROE probability distributions for a “representative” bank. The distributions are conditional on determinants based on unbalanced quantile regressions for 109 SSM banks over 2007–2016 (which include bank and time fixed effect terms). y-axis has been scaled by 100.