Frequency of Financial Crises
Even if the costs of financial crises could be estimated with precision and reliability, these costs would have to be paired with estimates of the frequency of crises to arrive at an estimate of the benefit from regulations that reduce crises' frequency. This modeling faces similar challenges as estimating effects: subjectivity in selection among relatively small numbers of historical data points and sensitivity of results to choice of data points. The Basel Committee simply took average frequencies from two studies (318) over an arbitrarily chosen period and set of countries (1985 to 2009 for G10 and BCBS countries, except Russia and China, which were included from 1992 on) and made the heroic assumption that this average was a good estimate of the probability of a crisis for any given year and country. (319)
The FSA, by contrast, used a longer time period (1970 to 2007), a narrower set of countries (OECD countries), and relied on a multivariable logit approach relating the likelihood of a crisis in a given year "to a vector of explanatory variables," with observed crises in the past coded one and non-crisis years coded zero. (320) This approach relies on the logistic cumulative distribution to predict future crises and is an improvement over BCBS 173 if interdependencies among time-varying observables affect crisis frequency, as seems likely. For example, housing prices have varied over time, and crises often coincide with (partly causing, partly being caused by) bubbles in housing prices, so crisis odds would not be uniform over time but would vary in cycles and across countries. However, the small number of crises that can be modeled this way (FSA 38's data included fourteen) limits the value of this approach, in statistical degrees of freedom and in robustness, and the functional form imposes assumptions on the shape of the distribution of crisis probabilities that is nowhere defended in the FSA's publications.
Because of differences in approach, the FSA's results differ markedly from the Committee's results. BCBS 173 reports an estimated baseline probability of a crisis per year for all countries of 4.5%. (321) FSA 38 reports a baseline probability ranging from 0.7% (for Germany) to 21.7% (for the United Kingdom)--that is, from one-sixth to five times the estimate used by BCBS (173). (322) Again, the sensitivity of outputs to assumptions illustrates how fragile CBA/FR of capital regulation remains. (323)
Effects of Higher Capital Requirements on Financial Crises
A third task necessary to estimate the benefits of higher capital requirements is to estimate how higher capital will affect the frequency and effects of future crises. The challenges are similar to those outlined in the case studies of SOX and mutual fund governance above, if slightly less difficult. The challenges are less difficult because capital levels have a more mechanical relationship to bank failure than disclosure and governance regulations have to fraud and fund performance, respectively. If a bank's capital falls below zero, it is by definition insolvent and will be either closed, nationalized, or bailed out (and/or suffer a bank run)--all of which (at least by most definitions) feed directly into the occurrence of a financial crisis.
Nevertheless, the modeling exercise remains difficult here, too, and includes a long list of challenges. Three are reviewed here: (1) baselines; (2) packages; and (3) international externalities. (324) The first question in any CBA is what baseline to use. Similar to the effect of fraud revelation on disclosure practices in the SOX case study, financial crises stimulate banks to raise their capital levels even without regulatory reform, as private actors increase the price of lending or investing in now apparently riskier banks. So how should one measure the effect of a regulatory mandate for new capital--against the baseline of pre-crisis capital levels, or against levels that could be expected in the wake of the crisis without the regulation? The argument for the former-advanced in FSA 42--is that "banks will tend to relax their post-crisis holdings of capital as the economic cycle strengthens." (325) This seems sensible as a rough prediction, but it is not anchored in an equilibrium model of bank behavior. After all, banks observe the same indicia of the probability of a crisis as used in the FSA's CBA/FR of Basel III. Bank investors can observe those indicia and bank capital levels, so why should we assume that bank capital levels only subside, rather than rise and fall as the risk of a systemic crisis rises and falls? It may be that private actors lack sufficient incentives to demand that an optimal level of capital be retained by banks, but for CBA/FR of capital requirements, the baseline itself--the capital that private actors would demand--is likely to change over time in unpredictable ways.
Part of the reason that private actors may lack incentives to demand that banks retain optimal capital is that they face moral hazard due to the likelihood of bailouts and other policy interventions. But that fact calls into question the validity of using pre-crisis capital levels as appropriate baselines altogether. Has moral hazard increased, decreased, or remained the same after the bailouts of 2008 P Lehman failed, and Bear Stearns and Merrill Lynch were forced to sell at fire-sale prices--so perhaps investors are now less certain about future bailouts. But, of course, more than (700) U.S. banks were bailed out, (326) not to mention the indirect bailouts through the various liquidity facilities established by the Federal Reserve Board--so perhaps investors face even more moral hazard than before. FSA 42 asserts that the pre-crisis period was one in which "banks' decisions ... were not distorted by the immediate influence of the crisis or regulators' response to the crisis." (327) But it presents no evidence to support that assertion. Any rational actor who anticipates a crisis should, given policy responses to past crises, also anticipate that a bailout may occur with some probability, and the capital levels it will demand will be affected by that anticipation. The better point, then, is that a model of the effect of future capital regulation should start with a baseline that explicitly takes into account moral hazard as a permanent condition of financial markets without adequate regulation. However, establishing such a baseline would require estimating the subsidy provided by the moral hazard to bank investors--a task not yet convincingly tackled by researchers.
Another challenge is that Basel III consists of a package of reforms, not one reform. As FSA 42 notes, if the probability of a crisis is non-linear in the level of bank capital, as assumed in a logit model (and as seems likely), then the effect on that probability of each piece of the reform package will depend on the sequence in which the pieces are adopted. (328) As with SOX, the best one may be able to do in estimating the causal impact of a package of reforms is to evaluate the package as a whole. For the CBA/FR of any given package of reforms, this is not a critical problem, but it does undermine the value of CBA/FR because it allows regulators to determine (to an extent) what is being evaluated--and may allow a package to include some reforms that are net positive (if evaluated on their own) with other reforms that are net negative (if evaluated on their own), as long as the former outweigh the latter.
A third challenge to estimating the causal impact of Basel III, also noted in FSA 42, (329) is that it is a voluntary multilateral initiative, which means that it will be implemented in different ways at different times in different countries. Implementation in one country will affect how banks in other countries act, independent of the effect of implementation by their own regulators. If, for example, U.K. banks are required to increase capital, they may not only reduce lending but focus continued lending on geographies or sectors where interest margins are highest, which in turn may affect currency and trade flows. An increase in U.S. capital regulation under Basel III, being evaluated in a CBA/FR by a U.S. regulator, should take into account the simultaneous shift in lending activity by U.K. banks, as well as the direct effect on U.S. banks. In a global financial market, the externalities of regulation create modeling difficulties of their own--adding yet more necessary assumptions regarding how the regulations will actually affect the probability or impact of future crises.
Costs of Higher Capital Requirements: Less Lending?
Finally, the costs of higher capital requirements must be estimated. The standard framework, employed by the Basel Committee and the FSA, (330) is to assume that a bank required to hold an increased amount of capital will raise corporate borrowing costs and so cut lending. The reasoning is simple: banks must pay their investors a minimum expected rate of return on their invested capital; if more capital is required, the bank will have to generate greater return; to generate a higher return, a bank must charge more to its borrowers; at a higher cost of borrowing, less lending will occur. The model further assumes that with lower lending by banks, economic output will fall.
As with the models of the benefits of capital requirements, however, models of the effects on the amount of lending (and its knock-on effects on output) require numerous contestable assumptions, and their outputs are sensitive to those assumptions. Among the assumptions are: (a) the cost of bank equity and whether it will fall in response to the change in capital levels required by the rule; (b) the ability of borrowers to substitute among different sources of financing (and at what cost); and (c) how non-bank sources will be affected by an increase in bank capital requirements and the reduction in...
Cost-benefit analysis of financial regulation: case studies and implications.
|Author:||Coates, John C., IV|
|Position:||III. How Might CBA of Financial Regulation Work? through C. Case Study #3: Heightened Capital Requirements for Banks 4. Frequency of Financial Crises through Conclusion, with footnotes and tables, p. 968-1011|
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COPYRIGHT GALE, Cengage Learning. All rights reserved.