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Testing for the underlying dynamics of bank capital buffer and performance nexus

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Abstract

This paper reveals the underlying dynamics between the capital buffer and bank performance in EU-27 countries. A dynamic panel analysis shows that capital buffer is significantly affected by bank performance and risk exposure. Remarkably, a threshold analysis identifies regime changes for the underlying relationships during the financial crisis of 2008. We find a positive relationship between the capital buffer and performance for banks that fall in the low performance regime, while a negative relationship is reported for the banks that belong to the high regime. Threshold results also show that buffer exerts a positive impact on bank performance. Although regulation reforms that aim to raise the capital requirements could improve bank performance and stability, these improvements are not homogeneous across banks.

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Notes

  1. Altunbas et al. (2007) measure bank capital as the ratio of equity over total assets.

  2. Consistent with this theory, Jacques and Nigro (1997) document a negative association between changes in capital and risk during the first year of the risk-based standards. The authors note that such a result might be due to the methodological issues in the risk-based guidelines where the weights assigned to assets classes might not reflect the true risk.

  3. In line with this theory, Baumann and Nier (2003) employing a sample of listed banks across 32 countries for the period between 1993 and 2000, find that banks located in countries with greater government support and deposit insurance hold lower capital buffer.

  4. In our sample, we include both saving and commercial banks following the study of Casu and Girardone (2010). The authors suggest that mainly commercial and saving banks in European Union form depositary institutions and they have a sufficient degree of cross-country homogeneity and comparability. Previous studies that include both saving and commercial banks in their analysis are Gropp and Heider (2010) and Kalyvas and Mamatzakis (2014). In order to account for any differences in the business model between saving and commercial banks, most of these studies employ a dummy variable. In line with these studies, we also include a dummy variable for commercial banks (COM).

  5. There are some concerns regarding the Z-Score. First, it depends on the quality of accounting framework and second, firms may smooth their accounting data and this, in turn, could lead to overassessment of the bank stability. Data availability issues dictate the choice of our proxies of bank risk exposure. Future research shall opt additional data sets such as Fitch or Capital IQ to estimate alternatives to Z-score.

  6. In this paper with use the xtbond2 stata command that implements the two-step system GMM estimator with the Windmeijer (2005) correction to the reported standard errors. In the one-step system GMM robust standard errors are reported which are robust to heteroscedasticity. In two-step GMM error terms are already robust and Windmeijer (2005) correction is implemented to standard errors. Two-step uses the consistent variance co-variance matrix from first step GMM to reconstruct the weight matrix. Without this correction, the standard errors tend to be downward biased.

  7. Franchise or charter value of a bank is defined as the value that would be foregone due to a bankruptcy. According to this theory there is ambiguous relationship between bank capital and risk taking. The higher risk can increase the probability of default and therefore encourage banks to raise their capital. This has been broadly discussed by Boot and Schmeits (2000).

  8. Banks that violate the minimum capital requirements lose part of their charter value (Flannery and Rangan 2008; Stolz and Wedow 2011). Thus, larger banks will take advantage of the economies of scale, diversification effects and the easier access to capital markets to maintain a higher capital buffer.

  9. Alfon et al. (2004), Ayuso et al. (2004) and Jokipii and Milne (2008) document a negative association between capital and past values of the return on equity. In this strand of literature the return on equity is used as an indicator of bank’s cost of raising equity capital. However, in this study and consistent with Berger (1995), Nier and Baumann (2006) and Flannery and Rangan (2008) the return on equity is used as an indicator of firm profitability.

  10. This finding is supported by Stiroh and Rumble (2006) who show that size is negatively correlated with efficiency for both domestic and foreign banks. The authors explain this relation through the agency costs, bureaucratic processes and other costs of managing extremely large institutions.

  11. Results are available upon request. Note that the ordering of variables could also be of importance. We test for the reverse ordering and results remain similar. Results are available under request.

  12. Note that without loss of generality we could estimate a panel VAR 4 × 4, and so on.

  13. Following Love and Zicchino (2006) we apply the Helmert procedure in the data set. That is the data we are forward mean differenced.

  14. As the ordering of variables in the panel VAR is not without significance we also estimate the system of equations, opting for the reverse ordering of variables. Results remain are available under request and confirm the present findings.

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Authors and Affiliations

  1. Nottingham Business School, Nottingham Trent University, 50 Shakespeare Street, Nottingham, NG1 4FQ, UK

    Anachit Bagntasarian

  2. Rennes School of Business, 2 rue Robert d’Arbrissel, 35065, Rennes, France

    Emmanuel Mamatzakis

  3. Department of Finance, School of Business, Management and Economics, University of Sussex, Jubilee Building, Falmer, BN1 9SL, UK

    Emmanuel Mamatzakis

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  1. Anachit Bagntasarian
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  2. Emmanuel Mamatzakis
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Correspondence to Anachit Bagntasarian.

Appendix

Appendix

See Table 17.

Table 17 Variable definitions and data sources
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Bagntasarian, A., Mamatzakis, E. Testing for the underlying dynamics of bank capital buffer and performance nexus. Rev Quant Finan Acc 52, 347–380 (2019). https://doi.org/10.1007/s11156-018-0712-y

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