Safety-net benefits conferred on difficult-to-fail-and-unwind banks in the US and EU before and during the great recession: A summary

Santiago Carbó-Valverde, Edward Kane, Francisco Rodríguez Fernández

22 March 2011



Accounting standards for recognising losses make it hard to detect if a bank is going under. The signs of a bank’s insolvency are slow to surface. During the housing and securitisation bubbles that preceded the 2007-2008 financial meltdown, top managers and regulators of US and EU financial institutions claimed that there was no way they could see the build-up of crisis pressures.

Moreover, as the crisis unfolded, these same officials failed to offer timely estimates of the financial and distributional costs of bailing out firms that benefited from open-bank assistance. The result is simple.

  • These observational difficulties encourage firms that are large, complex, and politically powerful to plan to shift their deepest downside risks onto taxpayers through the financial safety net.
  • The predictability of officials’ panicky willingness in crisis situations to acquiesce in these plans gives banking organisations that are difficult to fail and difficult to unwind what can be termed a “taxpayer put”.

Unless it is perfectly administered and adequately priced, this put supplies intangible capital to every firm that safety-net managers may be expected to protect.

Although these taxpayer puts do not trade directly, contingent-claims analysis offers several ways to estimate their value synthetically from the stock prices of individual systemically-risky firms. Extending research by Merton (1977) and Duan et al. (1992), our recent paper (Carbo-Valverde et al. 2011) uses one such method to examine the flow of ex-ante benefits that taxpayer puts generated for members of a large sample of US and European banking firms before and during the Great Recession. Our study defines a firm’s safety-net benefits as the implicit value of the per dollar, pound, or euro insurance premium percentage that perfectly informed and incentive-unconflicted officials would collect from a protected firm in exchange for its access to taxpayer credit support.

The model used has two equations.

  • It generates insurance premium percentage as a positive function of an institution’s leverage and portfolio risk (where portfolio risk is proxied by the volatility of equity returns).
  • The second equation features a trade-off between leverage and volatility that captures potential constraints on insurance-premium-percentage maximisation generated by market and regulatory discipline and by managerial career concerns.

Model parameters are estimated with annual data taken from the Bankscope database for the years 2003-2008. To assure that these estimates are robust, regression experiments introduce several control variables and span different intervals of time and different subsets of banks and countries.

The build-up of crisis pressures may be seen in the growing value of insurance premium percentage in pre-crisis years. Particular interest focuses on banks that either might be presumed to be difficult to fail and difficult to unwind ex ante or are revealed to be ex post. Significant differences in safety-net management emerge between the US and Europe, but in all regions and time frames these banks are shown to have received proportionately higher safety-net benefits than other banks. Introducing an explicit selection equation for banks that actually received open-bank assistance during the crisis years of 2007-2008 provides further evidence of differences in bailout decision-making between the US and Europe.

Our work suggests three important lessons:

  • The first concerns authorities’ convenient claim that crisis pressures could not be foreseen.

Despite being limited to annual data for key variables, changes in volatility and leverage consistently help to predict changes in the flow of safety-net benefits across different estimation procedures, regions, and time periods.

  • The second lesson is that the mean flow of ex ante benefits declined in the face of the increased public accountability generated by the greater transparency of ex post bailout expense.
  • Third, a cross-country proxy for susceptibility to regulatory capture (Transparency International’s index of perceived corruption) helps to explain safety-net benefits and bailout decisions in Europe.

These findings suggest that authorities could be incentivised to do a better job of controlling safety-net benefits if they expanded their information systems so that they could track insurance premium percentage in a timely and transparent manner. The stochastic and econometric plumbing underlying our equities-based estimates of volatility and safety-net benefits could obviously be improved by making use of richer stochastic processes and datasets based on the prices of debt and derivative instruments.

A useful first step would be to require bank managers to report data on earnings and net worth more frequently – under civil or even criminal penalties for fraud and negligent misrepresentation if they do not. Data on market capitalisation are publicly available in real time, as are data on stock-market returns. If the values of on-balance-sheet and off-balance-sheet positions were reported weekly or monthly to national authorities, rolling regression models could be used to estimate changes in the flow of safety-net benefits in ways that would allow regulators to observe and manage taxpayers’ stake in the safety net in a more timely and effective manner.


Carbo-Valverde, Santiago, Edward J Kane, and Francisco Rodriguez Fernandez (2011), “Safety-Net Benefits Conferred on Difficult-to-Fail-And-Unwind Banks in the US and EU Before and During the Great Recession”, NBER Working Paper 16787

Duan, J-C, Arthur F Moreau, and C William Sealey (1992), “Fixed-Rate Deposit Insurance and Risk-Shifting Behaviour at Commercial Banks”, Journal of Banking and Finance, 16:715-742.

Merton, Robert C (1977), “An Analytic Derivation of the Cost of Deposit Insurance and Loan Guarantees”, Journal of Banking and Finance, 1:3-11.



Topics:  Financial markets Global crisis International finance

Tags:  financial regulation, systemic risk, too-big-to-fail

Full Professor of Economics, University of Granada

Professor of Finance, Boston College

Professor of Economics, University of Granada