The Costs and Benefits of Bank Capital—A Review of the Literature †
2. Basel Committee Long-Term Economic Impact Analysis and Subsequent Studies
2.1. Stability Benefits of Bank Capital
2.2. Cost of a Banking Crisis
2.3. Capital Requirements and Bank Funding Costs
2.4. Impact of Higher Loan Spreads on GDP
3. Results from the Research Task Force Survey and Academic Literature
4. Preliminary Conclusions and Suggestions
4.1. Assessing the Combined Evidence
4.2. Possible Improvements
Conflicts of Interest
Appendix A. Long-Term Economic Impact Assessment Calibration
- The reduction in output in crisis periods relative to normal times is set to three different levels, depending on different assumptions of how a crisis affects trend growth. For the cases of no permanent effects, moderate permanent effects and large permanent effects, the output loss is set to 19%, 63%, and 158% of output in normal times (“normal output”), respectively;
- The opportunity cost of higher capital resources is estimated to be 0.09% of normal output;
- The benefit of reducing the amplitude of the business cycle was judged to be too uncertain to be included.
Appendix B. Benefits and Costs of Capital, Revisited30
Appendix B.1. Benefits of Bank Capital
Appendix B.1.1. Lower Probability of a Crisis?
|Loan growth||1.163 **|
|Δ Leverage ratio||5.356|
Appendix B.1.2. Lower Crisis Cost?
Appendix B.2. Costs of Bank Capital in Normal Times?
Appendix C. Competition and Regulatory Reform Interactions
Appendix D. Relation between Marginal Benefits and Optimal Levels of Capital
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In the original LEI as well as in later studies the analysis refers to capital held, so that it does not distinguish between the minimum capital requirement and additional capital that banks may hold in excess of the minimum requirement. See Dewatripont et al. (2016) for a discussion of the costs and benefits of bank capital requirements outside of this stabiliser/drag framework.
Miles et al. (2013) and Barth and Miller (2018) are the only papers published thus far in economics journals. Cline (2017) is a book published by the Peterson Institute. A working paper version is available at piie.com/system/files/documents/wp16-6.pdf. Barrell et al. (2009) is a notable precursor to the LEI. See also de Ramon et al. (2012).
To be able to compare BCBS (2010) with a given later study, k*—defined as TCE/Basel II RWA—should be converted to the capital measure used in that later study. The conversion of the BCBS (2010) estimate is specific to the country and time-period of interest. For example, Firestone et al. (2017) provide a conversion estimate of the BCBS optimal capital range—10–15% in TCE/RWA (Basel II)—to 9.3–15.5% in Tier 1/RWA (Basel III) space by using a cross-section of US banks. Brooke et al. (2015) provide a conversion estimate of the BCBS (2010) optimal capital number for the UK—assuming moderate permanent effects of crises, they estimate a range of 16–19% in Tier 1/RWA (Basel III) space using samples of Euro-area banks and UK banks.
The LEI study concludes that the unconditional, annual probability of a banking crisis over the 1985–2009 period for G10 countries is at 4–5%, based on Reinhart and Rogoff (2008) and Laeven and Valencia (2008) crisis dating. Cline (2017, p. 28) notes that over the 1977–2015 period the probability is 2.6%.
Rapid credit growth (high credit/GDP) is invariably a highly significant, positive predictor of crisis in top down models. That is notable, if not surprising, because slower credit growth is considered a cost or drag from higher capital requirements, i.e., credit growth enters both sides of the costs and benefit calculation.
Bordo et al. (2001) estimated that the cumulative costs of a crisis in the post-Bretton Woods era was 7% of GDP, but that assumes no permanent effects. Reinhart and Rogoff (2008) found the average peak-to-trough decline in GDP, which also assumes only temporary effects, following a financial crisis is 9.3%.
The interventions (suspended convertibility, recapitalisation, nationalisation, liquidity support, guarantees, or asset purchases) must also be sufficiently large to qualify as a crisis indicator: liquidity support of at least 5% of deposits and liabilities to non-residents, restructuring costs of at least 3% of GDP, asset purchases of at least 5% of GDP, significant bank nationalisations or bank guarantees.
The narrative approach involves a mix of judgment and rules. For example, a ‘minor crisis’ is identified by three characteristics: (1) OECD perception of significant financial sector problems; (2) a belief that the problems are significantly affecting aggregate credit supply or growth; and (3) a belief the problems are not so severe as to be central to recent macroeconomic events or current expectations.
The smaller, GLS (generalised least squares) estimate in the right panel may better apply to advanced economies as it down-weights smaller/less stable emerging economies.
Both stages use data from OECD countries from 1960 to 2008.
Brooke et al. (2015) also adapt the Romer and Romer method, extending their sample in time and eliminating countries that they judged were less relevant to the UK. They also make adjustments based on the expected effect of TLAC and other structural changes to the banking system. Like Romer and Romer, Brooke et al. (2015) examine the marginal impact of a financial crisis, i.e., the effect over and above the general recession element that would have occurred anyway. Separating the marginal additional cost of a financial crisis leads to a considerably lower estimate of the cost of a crisis and, therefore, a lower estimate for k*. Some studies have simply used the 2010 LEI estimates, relied on previous work, or used relatively simple assumptions to calibrate the cost of a crisis. The Federal Reserve Bank of Minneapolis (2017) used the high end of the BCBS (2010) range. Miles et al. (2013) assume that GDP falls by 10% the first year, 7.5% the next five years, and then 2.5% forever. Cline (2017) uses a parameterisation, distinguished by assumptions about forgone investment in capital and that capital’s depreciation. Barth and Miller (2018) roughly follow Miles et al. (2013). BIS (2015) uses two calibrations as alternatives: Cline (2017) and the original BCBS (2010) median. Almenberg et al. (2017) use an estimate of the cost of prior Swedish crises, acknowledging the great uncertainty around this estimate.
In addition, Brooke et al. (2015) find that crises would be around 25% more likely to happen absent effective resolution regimes, drawing on empirical studies which suggest that banks which expect to be bailed out are not therefore subject to market discipline and take more risk, raising the chance that a major bank will fail by around 30%.
If the higher cost of equity to banks reflects only the tax advantage of debt (and no other frictions), it is arguable whether the drag from higher required capital represents a social cost.
Almenberg et al. (2017) draw on the literature that estimates the effect of higher capital or capital requirements on lending spreads and does not estimate the MM offset directly. Fender and Lewrick (2016) use the same cost of capital and lending spread assumptions as those used in the LEI while acknowledging that they were likely highly conservative based on more recent work and revised the definition of capital. As a consequence, they use the LEI corrected by the conversion factor CET1/RWA = 0.78 TCE/RWA, hence the impact of 9 bps * (1/0.78) = 12 bps on GDP of a 1 percentage point increase in CET1/RWA.
If the cost of meeting the higher liquidity requirements (from the NSFR) is considered, the estimated median impact implies an additional 0.08% loss in steady state GDP, independently of the level of capital.
All units in this paragraph are per a one percent increase in the leverage ratio, while those in Table 1 are measured with respect to the risk-weighted ratio. Miles et al. (2013) conclude that a Tier 1 increase that would halve leverage would reduce equilibrium output by 0.15%. In their exercise, leverage—computed as assets/Tier 1 capital—falls from 30 to 15, which in Basel III terms would be a leverage ratio increasing from 3.3% to 6.6%. Assuming that leverage ratios increase as capital requirements increase and linearity, each percentage point increase in the leverage ratio would reduce equilibrium GDP by approximately one third (0.045%) of their estimate.
Other, more recent, LEI studies (see Section 2) are less conservative, assuming that the cost of equity is lower for better capitalised banks, and they therefore find a lower effect of bank capitalisation on banks’ overall cost of funding.
In some cases, estimates are approximate because values were derived from figures provided in the study. The full range of studies covered in Section 2 could not be included in these charts due to insufficient data availability in the respective studies.
Increases in loan spreads owing to capital increases used in subsequent LEI studies tended to be lower than the 13 basis points reported in LEI (Table 1). The mean of 12 basis points for this marginal effect in the piecemeal studies confirms the LEI estimate. (This is the average of standardised estimates reported in FRAME for Benetton et al. (2017), Cosimano and Hakura (2011), Dagher et al. (2016), Glancy and Kurtzman (2018), Santos and Winton (2013), Slovik and Cournede (2011), and Sutorova and Teply (2013)). We focus on marginal costs here rather than on its components because some studies use macroeconomic models that do not consider loan spreads.
Piecemeal studies (see FRAME standardised estimates for Covas and Driscoll (2014) and Locarno (2011)) with an average marginal cost of capital equal to 0.10% of GDP are consistent with the median marginal cost of capital used in BCBS (2010). The minimum marginal cost estimate in these piecemeal studies at 0.02% of GDP is in the lower range of those presented in Figure 8.
Recall that net marginal benefits (k) = reduced crisis probability (k) × crisis cost—output drag (loan spreads (k)). Generally, steeper net marginal benefit curves result in lower k* estimates.
Appendix D shows that using simple means of controlling for different capital ratios, by seeking to measure net benefits for a common capital ratio across studies, can still present difficulties when mapping comparisons of net benefits into conclusions about optimal capital.
For the cumulative net benefit, BCBS (2010) includes additional elements for the case where liquidity requirements are met. First, it has a one-off impact on the probability of a crisis (for an unchanged capital ratio), lowering it from 4.6% to 3.4% for a capital ratio of 7%. Second, it has a one-off cost of 0.08% of output in normal times. Both these elements are counted as part of the net benefit in BCBS (2010, Table 8).
The analysis presented in this appendix is joint work with Moritz Schularick (University of Bonn and New York University).
If banks raise loan rates, however, non-bank competitors may as well.
Competition may also indirectly influence k* by its effect on financial stability but whether increased competition increases or decreases financial stability is much debated both theoretically and empirically. See Martinez-Miera and Repullo (2010) for example. Zigraiova and Havranek (2016) review empirical studies in this literature and finds little interplay between competition and stability.
|Study||BCBS (2010)||Miles et al. (2013) (Economic Journal)||Brooke et al. (2015) (BoE)||Fender and Lewrick (2016) (BIS)||Firestone et al. (2017) (FRB)||Cline (2017) (Peterson Institute)||Barth and Miller (2018) (Journal of Financial Stability)||Federal Reserve Bank of Minneapolis (2017)||Almenberg et al. (2017) 1|
|Coverage||BCBS members||UK||UK||BCBS members||US||US, Japan, Western EU||US||US||Sweden|
|Assumptions||MM offset (%) 2||0||45||50||0||50||35–60||0||50||0|
|Discount rate (%)||5||2.5||3.5||5||2.7||1.5||5||5||0 to 3|
|Permanent crisis effects?||Range||Mostly (75%) temporary||Yes||Yes||Range||Yes||Mostly |
|Other reforms incorporated||Liquidity||TLAC, resolution||Liquidity, TLAC, resolution, ring-fencing||TLAC, resolution||Liquidity, TLAC, resolution||TLAC, resolution||None||None||TLAC|
|Approximate marginal benefits and costs of capital 3|
|Benefits||Reduced crisis probability |
(annual, %) 4
|Cost of crisis (discounted, annual GDP %)||19–158 (median: 63)||140||43||63–100||41–99||64||47||158||180|
|Costs||Increase in loan spreads (bp) 4||13||2.5||5–10||13||3–7||–||2.3||6||6|
|Cost of higher spreads |
(annual GDP bp) 4
|Optimum (T1/RWA % unless indicated)||10–15 6 (TCE/Basel II RWA)||16–20||10–14||10–11 (CET1/RWA)||13–25||12–14 (CET1/RWA)||25 7||23.5 |
|Bordo et al. (2001)||1880–2000||21 (later 56)||1 indicates crisis at date, 0 otherwise|
|Reinhart and Rogoff (2008)||1800–2008||66||1 indicates crisis at date, 0 otherwise|
|Laeven and Valencia (2012)||1970–2011||Global||1 indicates crisis at date, 0 otherwise|
|Romer and Romer (2017b)||1967–2012||24 (OECD)||Continuous (1 to 15)|
|Jorda et al. (2017)||1870–2013||17 (OECD)||1 indicates crisis at date, 0 otherwise|
|Study||Other Reforms Considered and Effects|
|BCBS (2010)||NSFR reduces crisis probability 1.2 percentage points to 1.5 percentage points given 10% liquidity, with smaller effects at higher capital levels.|
|Brooke et al. (2015)||TLAC requirements; an enhanced resolution regime (including, implicitly, the effects of the UK ring-fencing structural reform policy); new Bank of England liquidity regime and liquidity regulations. Joint effect reduces k* by 5 percentage points.|
|Firestone et al. (2017)||Higher liquidity reduces crisis probability, but minimal effect for capital over 10%; TLAC reduces crisis length and expected cost by 4% of GDP. Small effect on k*.|
|BIS (2015)||TLAC reduces crisis probability and cost; reduces net benefits of increased capital from 2% to 1% of GDP.|
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Birn, M.; de Bandt, O.; Firestone, S.; Gutiérrez Girault, M.; Hancock, D.; Krogh, T.; Mio, H.; Morgan, D.P.; Palvia, A.; Scalone, V.; et al. The Costs and Benefits of Bank Capital—A Review of the Literature. J. Risk Financial Manag. 2020, 13, 74. https://doi.org/10.3390/jrfm13040074
Birn M, de Bandt O, Firestone S, Gutiérrez Girault M, Hancock D, Krogh T, Mio H, Morgan DP, Palvia A, Scalone V, et al. The Costs and Benefits of Bank Capital—A Review of the Literature. Journal of Risk and Financial Management. 2020; 13(4):74. https://doi.org/10.3390/jrfm13040074Chicago/Turabian Style
Birn, Martin, Olivier de Bandt, Simon Firestone, Matías Gutiérrez Girault, Diana Hancock, Tord Krogh, Hitoshi Mio, Donald P. Morgan, Ajay Palvia, Valerio Scalone, and et al. 2020. "The Costs and Benefits of Bank Capital—A Review of the Literature" Journal of Risk and Financial Management 13, no. 4: 74. https://doi.org/10.3390/jrfm13040074