The implicit subsidy of banks

Joseph Noss, Rhiannon Sowerbutts, 17 June 2012

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The experience of the crisis has revealed that a credible threat of failure does not always exist for banks. While equity holdings were severely diluted through state intervention, debt holders of some failed banks did not incur losses and were guaranteed by governments. To the extent that neither banks nor their creditors paid for this guarantee, it can be considered an implicit subsidy.

The implicit subsidy of banks represents a transfer of resources from one set of agents — the government (and ultimately taxpayers) — to the financial sector. The distribution of the benefits depends on the underlying competitive structure of the banking industry, scarcity of its resources and the precise nature of the change in incentives that the subsidy induces. But it seems likely that bank creditors, customers, staff and shareholders all benefit to some degree, at the expense of taxpayers.

Quantifying the implicit subsidy to banks has generated considerable interest. The numbers are striking, both in their sheer scale, but also in their variation. Estimates of the implicit subsidy to major UK banks vary from around £6 billion (Oxera 2011) to over £100 billion (Bank of England 2010). The key contribution of our paper (Noss and Sowerbutts 2012) is to set out the two main approaches, their merits, and propose a new method of estimation.

Quantifying the subsidy

Unlike other types of explicit financial obligation, an implicit subsidy has neither transparent terms nor an observable price. This complicates its measurement. Existing approaches to the quantification of the implicit subsidy can be split into two types.

  • ‘Funding advantage’ models which value the subsidy as the aggregate reduction in the cost of bank funding due to an implicit government guarantee;
  • ‘Contingent claims’ models which value the subsidy as the expected payment from the government to the banking system necessary to prevent default.

Funding-advantage models compare the cost a bank faces in issuing its debt with a higher counterfactual cost that it would face in the absence of implicit government support. The subsidy across the entire banking system is obtained by adding up the individual banks’ subsidies, which are calculated for each bank individually.

We produce estimates for the implicit subsidy for major UK banks from 2007-2010 using a funding-advantage approach, based on two types of ratings. This compares a bank’s actual cost of funding (reflecting its ‘support’ rating) with an estimate of the higher cost of funding a bank would face in the absence of the implicit guarantee (consistent with its ‘stand-alone’ rating) (Figure 1). The subsidy increased notably between 2008 and 2009 due to increases in the perceived likelihood of government intervention and in banks’ cost of funding.

Figure 1. Average ratings uplift(a) and the implicit subsidy of major UK banks calculated under the (ratings-based) funding advantage model.(b)

Source: Bank of America, Merrill Lynch, Capital IQ, Moody’s and Bank calculations. Adapted from Noss and Sowerbutts (2012).

(a) Ratings uplift is defined as the number of Moody’s ratings categories by which the support rating exceeds that of the standalone.

(b) Aggregate implicit subsidy of Barclays, HSBC UK, LBG and RBS.

Contingent-claims models calculate the implicit subsidy across all banks in aggregate. They estimate it as the expected annual payment from the government to subsidised banks necessary to prevent their default. This is modelled as the shortfall between the value of banks’ assets and some ‘threshold’, based on their minimum capital requirements at some future time. Failure is assumed to arise when the total assets of all banks fall below this minimum requirement. The value of government support is assumed to be the sum necessary to restore the value of assets to this minimum amount, weighted by the probability of their falling below it.

We explore two different contingent-claims methods in depth in our paper:

  • Option-price approach: This models the future distribution of the value of banks’ assets based on the prices of options written upon its equity (Oxera 2011).
  • Historical approach: We also propose a new method of estimating the subsidy based on the historical distribution of observed equity price movements.

The implicit subsidy of major UK banks estimated using both the options-based and historical contingent-claims approaches are compared with those of the funding advantage (ratings-based) approach (Figure 2). The range of estimates is broad. The funding-advantage approach estimates the implicit subsidy in 2010 to be around £40 billion. The historical and options-based contingent claims methods produce estimates of around £30 billion and £120 billion.1  The results of the contingent claims approach are sensitive to underlying modelling assumptions, resulting in a divergence in estimates.

Figure 2. The implicit subsidy of major UK banks in 2010 as measured by the funding-advantage and contingent claims approaches(a)(b)

(a) Both the historical and options-based contingent claims approaches model the subsidy as a look-back option discounted at a rate of 1.2%.

(b) Aggregate implicit subsidy of Barclays, HSBC UK, LBG and RBS.

Source: Adapted from Noss and Sowerbutts (2012).

Figure 3 compares time series of estimates of the implicit subsidy based on the funding advantage and contingent claims (historical) methods. These are broadly comparable in 2009/10 but diverge in 2007/08. In 2007, and for most of 2008, rating agencies assumed there to be almost no difference between the stand-alone and support ratings of most UK banks, which is one reason why the funding-advantage estimates are low. In contrast, estimates based on the (historical) contingent-claims method vary significantly from year to year, as the observed distribution of banks’ equity prices — and associated implied ‘tail risk’ of bank failure — changes significantly over time. The very high estimate of the implicit subsidy in 2008 is driven by the exceptionally-high volatility of equity prices in the later part of that year. Estimates of the implicit subsidy for this period could be seen as an upper bound on its value, since the volatility of equity prices was also driven by, for example, high levels of investor risk aversion.

Figure 3. Variation in the implicit subsidy over time

Source: Adapted from Noss and Sowerbutts (2012).

Conclusion

The range of results from using funding advantage and two types of contingent-claims methods reflects their relative strengths and the information on which they draw. Funding advantage approaches rely on subjective ratings-agency judgement to determine the likelihood of bank failure and the probability of the extension of government support. In contrast the contingent-claims approach bases this estimate of the likelihood of bank failure and support on information from financial-market prices, and make the simplifying assumption that banks fail when assets fall to a value commensurate with banks’ minimum capital ratios, leading to the extension of government support.

Neither approach provides a perfect measure of the subsidy. Finding a definitive measure of the subsidy is frustrated due to its terms, and lack of observable price. But despite their differences, all measures point to significant transfers of resources from the government to the banking system.

References

Bank of England (2010), Financial Stability Report, December 2010.

Noss, J and Sowerbutts, R (2012), “The Implicit Subsidy of Banks”, Bank of England Financial Stability Paper 15.

Oxera (2011), "Assessing state support to the UK banking sector", Mimeo.

 

Disclaimer: The views expressed here are those of the authors and do not necessarily represent those of the institutions with which they are affiliated.


1These results value the subsidy as a look-back option discounted at a rate of 1.2% calibrated to the distribution of bank equity prices during 2010.

Topics: Financial markets
Tags: banks, implicit subsidy, UK

Senior Economist, Bank of England

Financial stability economist, Bank of England