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An analysis of the potential impact of heightened capital requirements on banks’ cost of capital

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Abstract

We provide new estimates of the association between the level of capital and the cost of capital for US banks by using the implied cost of capital as a measure of the cost of equity and by factoring in the effect of the cost of debt. With the important exception of the largest banks, we find that the cost of equity declines when the level of capital increases. This negative association is stronger after the onset of the 2007–2008 financial crisis. Banks’ cost of debt also declines when the level of capital increases. However, the weighted average cost of capital (WACC) remains unaltered when capital increases. The analysis of a sample of large banks yields different results: there is no discernible association between the level of capital and the costs of equity and debt for large banks, and their WACC increases with the level of capital.

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Data Availability

The datasets in this current study are not publicly available but are available from the corresponding author on reasonable request.

Notes

  1. The different views of the potential effect of increasing capital requirements can be summarized by the reactions to regulation requiring a risk-based capital surcharge on systemically important U.S. bank holding companies. The Fed Chairwoman Janet Yellen commented that this surcharge was necessary to “bear the costs that their failure would impose on others.” Tim Pawlenty, the president of The Financial Services Roundtable, which is a trade group that represents big banks, said: “Regulators should reasonably address risk, but this rule will keep billions of dollars out of the economy.”.

  2. For example, according to a former director of JP Morgan, “the first-order effect of increasing the ratio of common equity to total assets from 5 to 30% would clearly be very high. Assume that the annual cost of bank equity is 5 percentage points higher than the after-tax cost of bank deposits and debt…” (Elliott 2013).

  3. We eliminate 24 banks that have a CRSP's permanent company identifier corresponding to more than one RSSD code. As in Baker and Wurgler (2015), we exclude Federal Reserve banks, foreign banks, functions related to deposit banking, non-depository credit institutions, and federal credit agencies.

  4. However, these high levels of capital do not imply that regulatory capital is not binding for the majority of banks in our sample. We only observed the constrained choice of the level of capital. The optimal level may be lower, but banks may maintain capital above the regulatory level as a buffer against negative shocks that can push their regulatory capital below the minimum level. These shocks would force banks to raise additional equity or to cut dividends (for a more detailed discussion, see Berger et al. 1995).

  5. Chava and Purnanandam (2010) contend that the ICC is by construction a forward-looking measure that captures the time variation in expected stock returns better than ex-post realized returns. Contrary to the negative cross-sectional relation between expected default risks and stock returns found in other studies that use realized returns, Chava and Purnanandam (2010) find a positive relation using the ICC.

  6. Negative ICCs, which account for about 0.52% of the observations, are excluded from the sample. Other studies have matched earnings forecasts with market values at the end of an arbitrary month. For example, Gebhardt et al. (2001) use the end of April, while Hou et al. (2012) use the end of June. The choice does not take into account firms’ fiscal year. More importantly, using only one month per year imposes a significant loss of information. To ameliorate these concerns, we utilize monthly information from IBES, and then compute the average ICC for each quarter.

  7. A concern with the ICC is that the potential of mergers in the banking industry can be reflected in market prices, which may impact the ICC. This concern is more relevant before the 2007–2008 financial crisis, which was a period of significant consolidation in the banking industry. Furthermore, in the earlier stages of the financial crisis, investors and analysts failed to anticipate the magnitude of the crisis. Thus, market prices and analysts’ EPS forecasts were overstated, which can affect the accuracy of the ICC as a measure of the cost of equity.

  8. Bouwman et al. (2018) contend that behavioral theories (e.g., Gennaioli et al. 2015) can explain these results. Behavioral biases lead investors to underestimate the probability of bad times that results in low price spreads between well- and less-capitalized banks during good times. Investors gradually revise their beliefs during bad times, resulting in a gradual increase in the price spread between well- and less-capitalized banks.

  9. In the analysis of the ICC, several bank characteristics are statistically significant only before the crisis: the ICC increases with Ln Book value and Loan concentration and is negatively associated with banks’ ROE and Real estate loans. After the crisis there is a negative association between the ICC, Deposit to assets and Nonperforming loans. The coefficient for High VIX is negative before the crisis, but positive afterwards. These findings can be explained because market participants assign a low value to risk during expansions and become more risk averse during contractions. In the analysis of the cost of debt, nonperforming loans are positively associated with banks’ cost of debt, but only after the crisis.

  10. For instance, in our sample, the average ETOA for banks in the 5th decile is 8.91%, the average cost of equity is 9%, and the average cost of debt is 2.71%. For banks in the 10th decile, the average ETOA is 15.24%, the average cost of equity is 8.6%, and the average cost of debt is 2.55%. Thus, on average, banks with more equity have lower costs of equity and debt. However, we do not find this association between equity and the WACC. The WACC for banks in the 5th decile is 3.27% (2.71% × 91.09% + 9% × 8.91%), and the WACC for the best-capitalized banks is 3.472% (2.55% × 84.76% + 8.6% × 15.24%). Consistent with the M&M theory, substituting equity for cheaper debt does not have a significant effect on the banks’ overall cost of capital in our sample.

  11. We also consider using banks’ weighted average effective state income tax rate, an IV proposed by Ashcraft (2008) and by Berger and Bouwman (2009, 2013). Schandlbauer (2017) finds that the state corporate income tax rate has a first order effect on banks’ capital structure. However, we cannot reject at conventional significance levels the null hypothesis that the coefficient of this measure equals zero in the reduced-form equation. The finding that the effective state tax rate is not correlated with the level of capital after considering the effect of other exogenous variables indicates that it is not a good IV candidate for bank capital in our sample.

  12. We use xtabond2 in Stata IC/15 to estimate the dynamic GMM regression. See subsection 3.3 and Appendix 1 in Wintoki et al. (2012) for a description of the implementation of xtabond2. We use the “collapse option” to reduce the proliferation of instruments.

  13. A caveat with this bailout argument proposed in the literature is that it requires that the market participants must presume that the government protects their investments, and banks will not repay the government for its support. However, investors lost the value of their investments in failed banks. We also know that government securities purchases and lending programs to support the financial system generated billions of dollars for taxpayers that indicate the majority of banks repaid the government for their support. Thus, investors overestimated the probability of bailouts in some well-known bank failures. However, we cannot exclude the bailout explanation because the government indeed intervened to protect the large financial institutions and the real economy. It is possible that investors in large financial institutions could have experienced larger losses without this government support.

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Acknowledgements

We are grateful to an anonymous referee and the editor, Mark Carey, for their helpful comments. We are also grateful to the participants at the 2017 Financial Management Association European Meetings, in Lisbon, for their suggestions.

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Authors and Affiliations

  1. Department of Finance, Insurance, Real Estate and Law, University of North Texas, 1167 Union Circle, Denton, TX, 76201, USA

    Tomas Mantecon

  2. Prince Sultan University, Riyadh, Saudi Arabia

    Adel Almomen

  3. Department of Accounting and Finance, Texas Woman’s University, Denton, TX, 76204, USA

    He Ren

  4. School of Business, State University of New York at New Paltz, New Paltz, NY, 12561, USA

    Yi Zheng

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Mantecon, T., Almomen, A., Ren, H. et al. An analysis of the potential impact of heightened capital requirements on banks’ cost of capital. J Financ Serv Res 64, 325–368 (2023). https://doi.org/10.1007/s10693-023-00400-y

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