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Systemic risk-shifting in U.S. commercial banking

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Abstract

This paper puts forward the proposition that U.S. commercial banks use dividends as a mechanism to shift systemic risk to debt-holders and the deposit insurer. Using a mixed data sampling modeling approach, it is shown that monthly systemic risk factors are associated with a positive effect on future quarterly bank dividends indicating systemic risk-shifting. These factors include absorption (Kritzman et al. in MIT working paper, 2010), catfin (Allen et al. in Rev Financ Stud 25:3000–3036, 2012), covar (Adrian and Brunnermeier in CoVaR. NBER Working Paper 17454. National Bureau Economic Research, Cambridge, MA, 2011), delta_covar (Adrian and Brunnermeier 2011, mes (Acharya et al. in Rev Financ Stud 24:2166–2205, 2011b), real_vol (Giglio et al. in J Financ Econ 119:457–471, 2016), and size_con (Giglio et al. 2016). In addition, they can now-cast the upward trend in systemic risk-shifting in the 1990s and the downward trend from the early 2000s to 2007. The findings suggest that the rules governing bank dividends need be revised, support the imposition of a dividend tax to mitigate the negative externalities of dividends as a risk-shifting mechanism, and document a reduced effectiveness of Prompt Corrective Action in controlling risk-shifting.

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Notes

  1. Risk-taking, as distinct from risk-shifting, refers to the causal link from dividends to risk (Onali 2014).

  2. Citigroup cut its dividend only in November 2008, and JPMorgan and Wells Fargo as late as February and March 2009 respectively. Aggregate bank dividends paid at the third quarter of 2007 were $28 billion, and as late as 9 months into the crisis this amount was $18 billion. This is in contrast to the dividend policy by 61 firms in S&P 500, which drastically cut dividends in 2008.

  3. The dividend to assets ratio was used following a suggestion by an anonymous referee to focus on accounting-based measures. We wish to sincerely thank the referee for this point.

  4. We consider here the nonparametric method, in line with Giglio et al. (2016).

  5. Adding lags of \( Y_{t} \) to (14) generates a 'seasonal' response of Y to X (Ghysels et al. 2007). To resolve this issue, we follow Clements and Galvão (2008) to include autoregressive lags. We consider initially:\( Y_{t} = \alpha + \gamma \varPhi (\theta ,L^{1/12} )X_{t - 1}^{(12)} + \varepsilon_{t}^{(12)} \). We then take the residuals \( \hat{\varepsilon }_{t} \) and estimate the initial value for \( \beta \), \( \hat{\beta }_{0} \), from \( \hat{\beta }_{0} = (\sum {\hat{\varepsilon }_{t - 1}^{2} } )^{ - 1} \sum\limits_{{}}^{{}} {\hat{\varepsilon }_{t} \hat{\varepsilon }_{t - 1} } \). We next construct \( Y_{t}^{*} = Y_{\tau } - \widehat{{\beta_{0} }} Y_{\tau - 1} - \beta_{1} Y_{\tau - 2} - \widehat{{\hat{\delta }{\rm Z}_{\tau - 1} }} - \widehat{{\vartheta G_{t - 1} }} \), and \( X_{t - 1}^{*} = X_{t - 1} - \hat{\beta }_{0} X_{t - 2} \), and the estimator \( \hat{\theta } \) is obtained by applying nonlinear least squares to \( Y_{t}^{*} = \alpha + \gamma \varPhi (\theta ,L^{1/12} )X_{t - 1}^{*} + \varepsilon_{t}^{{}} \). A new value of \( \beta ,\hat{\beta }_{1} \), is obtained from the residuals of this regression. Then, using \( \theta ,\hat{\beta }_{1} \) as initial values we get the estimates of \( \theta ,\beta ,\delta ,\vartheta ,\gamma \) that minimize the sum of squared residuals (Clements and Galvão 2008).

  6. Standard errors are obtained using the inverse of the information matrix. The coefficient covariance was computed using the observed Hessian with a degrees of freedom correction (Ghysels et al. 2004).

  7. We also estimated models in which the quarterly lagged credit risk was added as an extra independent variable. Credit risk was measured by the ratio of loan loss provisions to total loans. In all estimations, the effect of credit risk was statistically insignificant and thus, for parsimony we excluded this variable.

  8. Kanas (2013) focused on default risk-shifting over 1984–2010 and found that this can be traced only during certain sub-periods, and not during others.

  9. This is similar to a company producing emissions which lower its own costs but pollute the environment.

  10. Another tax component, according to Acharya et al. (2009), should be for the expected losses upon default of the liabilities guaranteed by the government.

  11. We wish to thank an anonymous referee for drawing these issues to my attention.

  12. Banks receiving TARP aid were required to pay a dividend to government of 5% raising to 9% in 2013. Furthermore, common dividends cannot be increased without Treasury approval until 3 years after aid issuance (https://www.vedderprice.com/-/media/files/vedder-thinking/publications/2008/10/summary-of-tarp-capital-purchase-program/files/summary-of-tarp-capital-purchase-program/fileattachment/summary-of-tarp-capital-purchase-program.pdf).

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Authors and Affiliations

  1. University of Piraeus, Piraeus, Greece

    Angelos Kanas

  2. University of Sharjah, Sharjah, UAE

    Panagiotis D. Zervopoulos

  3. Scientific Committee, Parliamentary Budget Office, Hellenic Parliament, Athens, Greece

    Angelos Kanas

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  1. Angelos Kanas
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  2. Panagiotis D. Zervopoulos
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Correspondence to Angelos Kanas.

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Appendix

Appendix

See Figs. 2 and 3.

Fig. 2
figure 2

Monthly systemic risk factors, 1984–2011

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Fig. 3
figure 3

Quarterly dividend to assets ratio, default risk, real GDP growth, 1984–2011

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Kanas, A., Zervopoulos, P.D. Systemic risk-shifting in U.S. commercial banking. Rev Quant Finan Acc 54, 517–539 (2020). https://doi.org/10.1007/s11156-019-00797-5

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