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Banking crises and the design of safety nets
Journal of Banking & Finance 29 (2005) 143–159 www.elsevier.com/locate/econbase
Banking crises and the design of safety nets Glenn Hoggarth, Patricia Jackson, Erlend Nier
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Bank of England, Threadneedle Street, London EC2R 8AH, UK Available online 19 August 2004
Abstract Governments face conflicting objectives in terms of the provision and design of safety nets for banking systems. Safety nets may reduce market discipline and can thus increase the likelihood of a banking crisis. But safety nets are adopted because of the perceived benefits they will confer in either preventing a weak banking system from spilling over into a full-blown crisis or in enabling the government to handle a crisis more effectively. This paper provides evidence on the effects of government safety nets on both these aspects and discusses implications for policy. 2004 Elsevier B.V. All rights reserved. JEL Classification: G21; G28 Keywords: Deposit insurance; Banking crises
1. Introduction Governments face conflicting objectives in terms of the provision and design of safety nets for banking systems. They need to weigh the likely negative effects on market discipline and moral hazard against the possibly more positive effects that different features could have on the course of a crisis were one to develop. In this
*
Corresponding author. Tel.: +44207 6013239; fax: +44207 6013217. E-mail address: [email protected] (E. Nier).
0378-4266/$ - see front matter 2004 Elsevier B.V. All rights reserved. doi:10.1016/j.jbankfin.2004.06.019
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paper, we examine whether support arrangements influence the likelihood of banking crises and then look at the effect that they have on the costs of resolution. The negative effects of safety nets are well understood. A number of theoretical contributions have focussed on the effect of safety nets on shareholdersÕ incentives to take excessive risk. In the seminal study, Merton (1977) showed that flat rate deposit protection schemes create a subsidy that is more valuable if a bank engages in riskier activities. However, safety nets are adopted because of the perceived benefits they will confer in either preventing a weak banking system from spilling over into a full-blown crisis or in enabling the government to handle a crisis more effectively. The banking crises over the 1980s and 1990s led a large number of countries to rethink their safety net arrangements and consider for example introducing explicit deposit protection schemes (Garcia, 1999; Demirgu¨c¸-Kunt and Kane, 2002). An important policy issue therefore is what (if any) benefits stem from the particular features of safety nets. We first examine the effect of different types of safety nets on the likelihood of banking crises. Within that, we look at the implications of market expectations that the government will support debtholders and then at the effect of different deposit protection arrangements. As regards the latter, we distinguish between: (a) no explicit (but possibly an implicit) scheme; (b) an explicit scheme with limited coverage (and the effect of co-insurance where even within the limit the depositors do not receive 100% payout); (c) an explicit scheme with unlimited coverage. We find that an explicit unlimited deposit protection scheme increases the likelihood of banking crises. The next most likely group to have a crisis is that without any scheme ex ante, which might seem perverse. But most countries without an ex ante deposit protection scheme introduce blanket government guarantees during a crisis and this is therefore likely to be built into market expectations and to create moral hazard. The group least likely to experience a crisis is that with an explicit but limited deposit protection scheme, and within that group those countries that require depositors to co-insure. Pre-committing to providing only limited cover therefore appears effective in limiting moral hazard. We then examine the implications of different types of deposit protection arrangement for the resolution of crises, looking at fiscal cost and output losses. Here we find countries which offer explicit but unlimited schemes or no explicit scheme to have the highest fiscal costs of resolution – reflecting the use of widespread government guarantees during the crisis in these cases – but the lowest cost in terms of output forgone. From this a basic trade-off emerges. Countries with limited explicit schemes (and which therefore allow more losses to fall on depositors) suffer higher output losses than those countries which provide greater protection to depositors (either because of an explicit but unlimited scheme or de facto, through necessity, in the absence of an explicit scheme). But these countries are likely to gain in the longer term through the reduced likelihood of future crises.
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2. Safety nets and the likelihood of banking crises The effect of safety nets on the likelihood of systemic banking crises is ambiguous a priori. Safety nets may increase moral hazard and weaken market discipline, which should make banking crises more likely. On the other hand it is possible that this negative influence could be outweighed if safety nets make vulnerable systems less prone to full-blown crises, i.e. reduce the likelihood of a crisis becoming systemic. We distinguish between two aspects of government safety nets: deposit insurance and implicit government support for the banksÕ creditors. Theory suggests two opposing ways in which deposit insurance might affect the likelihood of banking crises. First, broad deposit insurance may reduce the likelihood of bank runs. This channel is suggested by models such as Diamond and Dybvig (1983), where bank runs may occur in a bad equilibrium in which depositors may lose their confidence in the banking system even if banks are fundamentally sound. But it extends to models where the likelihood of a bank run is higher the weaker is the bank in terms of fundamental solvency, such as Bhattacharya and Jacklin (1988), etc. On the other hand, the moral hazard incentives induced by deposit insurance might encourage banks to increase the risk of default. 1 When banks are subject to the threat of a bank run, they may behave more prudently than they would if that threat was removed by a comprehensive deposit insurance scheme. More generally, deposit insurance may reduce the link between a bankÕs risk of default and its funding cost, creating an incentive for the bank to increase default risk at the expense of depositors or the deposit insurance fund. 2 As in the case of explicit deposit insurance, implicit government support may have two opposing implications for bank stability. First, government support may prevent severe problems in a banking system from actually culminating in a crisis – in other words the support could disguise the extent of weakness in the banks. Governments typically extend implicit support to their banking system precisely because they want to prevent a systemic crisis. On the other hand, implicit government support may result in moral hazard incentives for banks who may be tempted to exploit the implicit subsidy provided by the government by increasing their risk. This may increase the probability of banking problems developing. A number of prior empirical studies examined the implications of deposit insurance on bank stability, e.g. Demirgu¨c¸-Kunt and Detragiache (2002), Eichengreen and Arteta (2000), Hovakimian et al. (2003), among others. The seminal study by Demirgu¨c¸-Kunt and Detragiache (2002) found, using a logit analysis, that the existence of deposit insurance increased the likelihood of crises, controlling for a number
1
Deposit insurance might also create moral hazard incentives for regulators. By reducing runs and liquidity problems at banks deposit insurarance may reduce pressure on regulators to resolve insolvencies promptly. 2 In principle, the funding charge adopted in deposit insurance schemes could be linked to a bankÕs relative riskiness. But in practice, this proves difficult, not least because banking risk is not easily observed or measured. As a result, the funding charge of the overwhelming majority of schemes is independent of a bankÕs riskiness, Demirgu¨c¸-Kunt and Kane (2002).
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of macro-variables. They also found that the adverse impact of deposit insurance on bank stability was stronger when the institutional environment was weak and that the impact of deposit insurance on bank stability tended to be stronger the more extensive was the coverage offered to depositors. Eichengreen and Areta (2000) used a different set of countries and a slightly different crisis definition. They found that, in contrast with the Demirgu¨c¸-Kunt and Detragiache (2002) finding, explicit deposit insurance decreased the likelihood of crises in their sample. 2.1. Empirical approach We use a data set 3 which covers 29 countries 4 over the years 1994–2001. According to Caprio and Klingebiel (2003), seven of these countries experienced a systemic banking crisis (defined as much or all of bank capital being exhausted) after 1993 – Korea, Thailand, Indonesia, Malaysia, Japan, Turkey and Argentina. In the case of the first four listed the onset of the crisis was in 1997/98. Turkey and Argentina experienced banking crisis that started in 2001 while JapanÕs crisis has been ongoing over the whole period. 5, 6 Using this dataset, we look at the extent to which the likelihood of a country experiencing a crisis after 1994 was affected by several aspects of the safety net in that country, controlling for initial macroeconomic conditions prevailing before the onset of the crisis. Demirgu¨c¸-Kunt and Sobaci (2000) provide a dataset on the existence and extent of deposit insurance schemes across countries. We use this to construct indices of the extent of depositor protection, focusing on those features that are likely to affect market discipline from depositors – co-insurance (i.e., less than 100% payout on the portion of deposits covered) and whether or not there is a limit on the pay-out receivable by depositors. In particular, we define explicit=1 if there exists an explicit deposit insurance scheme, =0 otherwise no co-insurance = 1 if there is an explicit scheme, specifying no co-insurance, =0 otherwise limited = 1 if there exists an explicit scheme, specifying no coverage limits, =0 otherwise.
3 The dataset is based on the bank-level dataset that was assembled by Baumann and Nier (2003) for a study of market discipline and bank risk-taking across countries. 4 These are Austria, Australia, Argentina, Belgium, Brazil, Canada, Chile, Finland, France, Germany, Indonesia, Ireland, Israel, Italy, Japan, Korea, Malaysia, the Netherlands, Norway, Poland, Portugal, Singapore, Spain, Sweden, Switzerland, Thailand, Turkey, the UK and the US. 5 The list of crisis countries includes Japan. This may raise questions regarding the endogeneity of the safety net variables. In particular, government support is measured at the end of the sample period. In Japan, measured government support is high, potentially due to the way the Japanese government responded to the crisis. In addition, unlimited deposit insurance was introduced only in 1996, arguably in response to the incipient crisis. On the other hand, anecdotal evidence suggests that, there had always been a presumption on the part of depositors and markets in Japan that banks would not be allowed to fail. All results are qualitatively unchanged if Japan is excluded from the list of crisis countries. 6 For the Nordic countries the onset of the crisis was before the start of the sample period.
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In addition to measuring explicit deposit insurance, we take account of the implicit support afforded to the banks by their government. The Fitch rating agency assigns a support rating that reflects the probability of support from a parent or the government. For most large, listed banks that were used to create the index for each country only the latter is important. The support rating ranges from 1 (near certain bail-out 7) to 5 (bail-out very unlikely). For each bank, Baumann and Nier (2003) constructed a measure of government support which takes the value 1 if the public support rating indicates that a bail-out is very likely (support rating equal to 1 or 2) and 0 if the public support rating indicates a low probability of a bail-out (rating is 3, 4, or 5). We use the country average of this variable as a measure of both the willingness and the ability (in fiscal terms) of the government in question to bail out its banks and their creditors and thus to prevent a systemic crisis. Probit regressions are then run on the following simple model of banking crises: crisis ¼ f ðSNet; ZÞ þ e;
ð1Þ
where ÔSNetÕ refers to aspects of the safety net and Z are control variables. Crisis is a country dummy variable that takes the value 1 if there has been a systemic banking crisis according to Caprio and Klingebiel (2003) and takes the value 0 otherwise. 8 Probit regressions recognise that crisis is defined as a zero-one event and are based on a model of the probability of banking crises. Table 4 in the Appendix gives an overview of the data for the safety net variables as well as the crisis dummy. The hypothesis we test using this regression model is whether safety net factors affect the likelihood of a banking crisis developing over the sample period, for given initial conditions (Z). 9 The list of variables that summarizes initial economic conditions includes the growth rate of GDP, the current account position in per cent of GDP, the short term interest rate, as well as per capita GDP, all as of 1994. A number of studies, e.g. Honohan (1997), have argued that crises often follow credit-driven booms, which are marked by high levels of GDP growth and large capital inflows. In addition, a number of studies document that crises tend to be preceded by high interest rates, e.g. Demirgu¨c¸-Kunt and Detragiache (2002). 10 Finally, Kane (2000) shows that across countries, measures of the strength of a countryÕs institutional environment–including the strength of its supervisory and regulatory regime – tend to increase with per capita GDP. 11
7
Fitch assumes that typically, shareholders will not be bailed out. The notion of support therefore refers to the likelihood of a creditor bail-out. 8 The resulting list of crisis countries is: Japan, Korea, Thailand, Indonesia, Malaysia, Turkey and Argentina. 9 This approach builds on Barth et al. (2002), who condition on the level of inflation prior to the crisis in cross-sectional probit regressions. 10 Mishkin (1996) argues that high interest rates were a factor contributing to the US savings and loans crises. But high interest rates may well also have played a role for some of the recent episodes of banking crises in emerging market economies, where policy interest rates were raised sharply to defend currency pegs. 11 See also Demirgu¨c¸-Kunt and Kane (2000).
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2.2. Results Table 1 summarises the main results. Note first that, while most macroeconomic control variables have a statistically weak effect on the likelihood of a banking crises developing, their signs appear plausible. In particular, a high growth of GDP and high capital inflows – associated with a current account deficit – tend to increase the likelihood of a crisis. High interest rates, likewise, tend to increase the likelihood of a crisis, while economic development, measured by per capita GDP tends to decrease it. As regards the safety net variables, it turns out that government support as measured by the average Fitch support rating for the banks in each country is statistically insignificant, but its negative sign suggests that the willingness and ability of Table 1 Impact of government safety nets on the likelihood of systemic banking crises Dep. variable: Crisis
Probit (1)
Support
0.9818 (0.3960)
Probit (2)
OLS (3)
Probit (4)
0.9611*** (0.0000)
Unlimited
2.2457** (0.0180)
Limited Limited with co-insurance Limited without co-insurance Implicit
GDP growth Current account Interest rate Constant
No. of obs Pseudo-R2 R-squared
OLS (6)
0.5159 (0.5930)
Explicit
GDP per cap
OLS (5)
0.0028 (0.9580) 1.5182 (0.9350) 0.0209 (0.1970) 0.0251 (0.6270) 0.5984 (0.7520)
0.0328 (0.5100) 5.1012 (0.7960) 0.014 (0.4140) 0.0141 (0.7960) 0.2002 (0.9340)
0.0078 (0.1620) 3.7920* (0.0630) 0.0026** (0.0500) 0.0001*** (0.0000) 0.1322 (0.4100)
27 0.3031
29 0.3071
29
P-values in parenthesis. * Statistical significance at the 10% level. ** Statistical significance at the 5% level. ***Statistical significance at the 1% level.
0.6525
0.0606 (0.2600) 13.2706 (0.5370) 0.0071 (0.5620) 0.0009 (0.6780) 2.0077 (0.3460) 29 0.572
0.9550*** (0.0000)
0.6865** (0.0280) 0.0068 (0.1780) 1.69 (0.3920) 0.0024 (0.1010) 0.0002*** (0.0000) 1.0995*** (0.0000)
1.0971*** (0.0000) 0.8558*** (0.0000) 0.7167** (0.0300) 0.0102* (0.0960) 1.8498 (0.3600) 0.0023* (0.0840) 0.0001*** (0.0030) 1.1550*** (0.0000)
29
29
0.6874
0.7248
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governments to bail out their banks may reduce the likelihood of a full-blown crisis, Table 1, Column 1. Also, the existence of an explicit deposit insurance scheme as such (as opposed to an implicit scheme) appears to have little effect on the incidence of a banking crisis, Column 2. If anything, the existence of a scheme appears to reduce the likelihood of a banking crisis, although this result is not statistically significant. This is in contrast with Demirgu¨c¸-Kunt and Detragiache (2002) who find in a sample of 61 countries between 1980 and 1997 that the existence of an explicit scheme increases the incidence of a banking crisis for countries that do not have an effective system of prudential regulation and supervision. However, like ours, their result is statistically weak and only just significant at the 10% level (with a P-value of 8%). 12 The reason for the conflicting results in different samples might be related to the fact that, on theoretical grounds the effect of an explicit scheme is ambiguous. On the one hand, an explicit scheme might reduce the likelihood of a depositor run, on the other hand an explicit scheme may remove the disciplining force of the threat of a run. Further, Gropp and Vesala (2001) argue that the introduction of an explicit scheme might even have beneficial incentive effects. Based on a European sample these authors show that the introduction of an explicit scheme may reduce moral hazard if deposit insurance credibly leaves out non-deposit creditors. This is because with a scheme in place governments may be more willing to let firms fail. To explore this argument in the context of our sample, we distinguish between explicit, but limited schemes and explicit unlimited schemes. Column 4 of Table 1 shows that countries with explicit, but limited schemes are far less likely to experience a crisis than are other countries in the sample, a result that is statistically significant at the 5% level. Column 3 of the same table suggests that countries with explicit unlimited schemes are more likely than other countries (including countries with no explicit schemes) to experience a banking crisis, where the result again is statistically strong. 13 This indicates that unlimited deposit protection schemes lead to less sound banking systems and that this outweighs any beneficial effects from the reduced incentives for depositors to run when the banking system is weak. The finding on unlimited schemes is in line with the result in Demirgu¨c¸-Kunt and Detragiache (2002) and underscores the moral hazard effects of this particular feature of the deposit insurance regime. Column 5 focuses on the effect of having no explicit (i.e. an implicit) scheme by introducing an additional dummy variables for such countries. Since a country either has no scheme, an explicit, but limited scheme, or an explicit and unlimited scheme, the latter category is omitted from the regression and all results are relative
12 Eichengreen and Areta (2000) examined the robustness of the Demirgu¨c¸-Kunt and Detragiache (2002) finding using a different set of countries and a slightly different crisis definition. Their results show a statistically negative coefficient, in contrast with the Demirgu¨c¸-Kunt and Detragiache (2002) finding. 13 In Columns 3, 5 and 6, inference is based on OLS rather than a probit regression. The reason is that convergence of the probit estimator was not achieved in these cases. The OLS regression applies a White correction for heteroskedasticity and P-values are based on robust standard errors. In addition, it turns out that for all models for which both estimators were feasible the results did not materially differ across estimation method.
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to that category. The regression suggests that, when compared to countries with an unlimited scheme, for countries with a limited scheme the likelihood of a banking crisis is reduced the most, but that countries with no (explicit) scheme are also less likely to experience a banking crisis than those countries with an explicit and unlimited scheme. Overall, this suggests a non-linear relationship as regards the effect of deposit insurance on the likelihood of crises. As compared to having no scheme, introducing an explicit scheme may well reduce the likelihood of a crisis. But the design of the scheme is important. Countries that offer unlimited protection are more likely to experience a crisis than countries that offer no explicit government support. The model presented in Table 1, Column 6 summarizes our results. It distinguishes between all three features – explicit versus implicit, limited versus unlimited as well as co-insurance versus no co-insurance – by introducing appropriate dummy variables. Again, the results are relative to the one omitted category, which is unlimited explicit insurance and they suggest the following ranking of the different possible regimes with respect to the likelihood of crisis. Countries with unlimited schemes are most likely to experience a crisis and those countries with no explicit scheme at all are significantly less likely to experience a crisis than this benchmark group. But the likelihood of a crisis is further reduced for those countries that have a limited depositor protection scheme. Among these countries, finally, the likelihood of crisis is the lowest for countries whose scheme includes a co-insurance element in addition to an absolute coverage limit.
3. The effect of safety nets on the costs of crises Although the evidence points to unlimited deposit protection schemes increasing the likelihood of crises, countries already vulnerable to a crisis may focus on the possible benefits in handling a crisis should it occur. Other countries might decide to remove any deposit protection arrangements in an attempt to maximise market discipline (e.g. New Zealand). A further important consideration is therefore the effect that various safety net arrangements may have on the ability of countries to manage and resolve a crisis and the resultant overall costs of crises. A number of recent empirical studies have assessed the impact of resolution techniques on the damage caused by crises. Dziobek and Pazarbasioglu (1997) find that most progress in restoring the banking systemÕs financial strength and its intermediation role occurs for countries that take action within one year of problems emerging. Kane and Klingebiel (2002) also emphasise that prompt intervention, especially where actions mimic market behaviour, minimises the damage caused by crises. Honohan and Klingebiel (2003) find in a sample of 40 developed country and emerging market crises that open-ended liquidity support and blanket guarantees increase the direct fiscal costs of crisis resolution. We consider the effect of ex ante arrangements such as limited and unlimited deposit protection schemes and expost measures introduced once a crisis has started such as government guarantees for depositors.
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The costs of banking crises are measured in two ways – a narrow measure based on estimates of the fiscal costs of crisis resolution and a broader measure proxied by the fall in output during the banking crisis period. Fiscal costs are the estimated net present value of the budgetary cost of the crisis based on official or expert assessment. These costs include both fiscal and quasi-fiscal outlays for financial restructuring including the recapitalization cost for banks, bailout costs related to covering depositors and creditors and debt relief schemes for bank borrowers. 14 These estimates may not be strictly comparable across countries. They may also overstate the final costs to the government to the extent they will receive future proceeds from re-privatisation and income from loan recoveries. Although Honohan and Klingebiel (2003) find that blanket government guarantees (and open-ended central bank liquidity support) are associated with higher fiscal costs of crisis resolution this does not imply necessarily causation. 15 Fiscal costs would be expected to be higher the larger the adverse shock to the banking system. But in face of such a potential systemic threat it is more likely that the authorities would also provide liquidity support and guarantees to liability holders. For example, full-blown systemic crises such as those in Japan, east Asia and in the Nordic countries would be expected to incur higher resolution costs together with government guarantees and LOLR, than smaller banking problems such as the US S&L crisis, Credit Lyonnais and the banking problems in Australia and New Zealand in the late 1980s. However, Honohan and Klingebiel include such episodes of banking problems as well as major crises in their sample. This suggests that comparisons of crisis intervention techniques and fiscal costs need to take account of the magnitude of the crisis. Second, even if intervention results in higher fiscal costs this needs to be weighed against the potential benefits to the wider economy from avoiding a systemic meltdown of the financial system. In the United StatesÕ banking crisis in the early 1930s the absence of depositor guarantees and liquidity support kept the fiscal costs low but at the expense of contributing to the marked decline in output at the time. Equations (1) and (2) in Table 2 show simple statistical relationships between fiscal costs and different ex ante insurance schemes in a sample of systemic crises – that is where the capital of the whole banking system was depleted or close to depletion. The amount of bank intermediation in the economy (measured by bank credit/GDP) and whether a currency crisis also occurred simultaneously are used as quantifiable proxies for the size of the banking crisis shock while GNP per head is used as a crude proxy for the ability of the financial system to withstand the shock. The results need to be treated with a degree of caution, because of the limited sample of crises (33) and the potential importance of country specific factors affecting the costs of crisis. Nonetheless, bearing these caveats in mind, controlling for other factors, it appears that countries that had in place an explicit scheme incurred lower fiscal 14
The data source is Honohan and Klingebiel (2003). Open-ended liquidity support is defined as liquidity support provided for more than 12 months which is greater than the aggregate capital of the banking system. Blanket guarantees are either explicit government guarantees or implicit ones proxied by where state banks account for more than 75% of the banking systemÕs assets. 15
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Table 2 Impact of explicit deposit insurance and government deposit guarantees on the fiscal costs (FCOSTS) and output losses (YLOSSES) of resolution in systemic banking crises Dependent variable
FCOSTS (1)
EXPLICIT DEPOSIT INSURANCE: UNLIMITED EXPLICIT DEPOSIT INSURANCE: LIMITED GOVERNMENT GUARANTEE CREDIT/GDP CURRENCY CRISIS GNP PER HEAD
R2 Number of observations
YLOSSES (2)
(3)
(4)
(5)
(6)
4.7 (0.32)
3.3 (0.56) 8.4* (0.07)
4.8 (0.22)
0.18** (0.04) 5.1 (0.28) 0.9 (0.11)
0.15* (0.07) 5.6 (0.21) 0.8* (0.09)
4.0 (0.22) 0.17** (0.05) 5.0 (0.29) 0.9* (0.09)
0.08 32
0.18 32
0.09 32
0.41*** (0.00) 9.5** (0.02) 0.5 (0.27)
0.43*** (0.00) 9.1** (0.03) 0.7* (0.10)
2.4 (0.56) 0.42*** (0.00) 8.8** (0.04) 0.8* (0.07)
0.60 31
0.60 31
0.58 31
Sources: World Bank database and Kyei (1995). FCOSTS: fiscal costs of resolution % of GDP. Sources: Caprio and Klingebiel (2003), Barth et al. (2002), IMF (2002), OECD (2002a,b). YLOSSES: cumulative deviation in the growth of GDP during the crisis period from its pre crisis 10 year trend. GOVERNMENT GUARANTEE: 1 where explicit blanket government guarantee or implicit one (where state banks account for 75% or more of banking system assets), 0 otherwise. Source: Honohan and Klingebiel (2003). CREDIT/GDP: Bank credit to the private sector/annual GDP (%). Source: IMF, International Financial Statistics. CURRENCY CRISIS: 1 where currency crisis, 0 otherwise. Currency crisis is a nominal depreciation (against the US dollar) of 25% combined with a 10% increase in the rate of depreciation in any year of the banking crisis period. Source: IMF, International Financial Statistics. GNP PER HEAD: GNP per head (US$000s, PPP) in the year that the banking crisis began. EXPLICIT DEPOSIT INSURANCE: 1 where an explicit deposit insurance scheme is in place before or during the crisis, 0 otherwise. UNLIMITED: 1 where an explicit but unlimited deposit insurance scheme is in place before or during the crisis, 0 otherwise. LIMITED: 1 where an explicit but limited deposit insurance scheme is in place before or during the crisis, 0 otherwise. P-values in parenthesis. * Statistical significance at the 10% level. ** Statistical significance at the 5% level. *** Statistical significance at the 1% level.
resolution costs than countries without an explicit scheme (see Table 3). However, this lower fiscal cost seems to be confined to schemes with a ceiling on the amount of deposits insured (Table 2, equation (2)) rather than schemes without a ceiling (equation (1)). This might imply that limited explicit schemes reduce the potential scope of bail out by making it clear ex ante which depositors would and would not be covered by the scheme in a crisis. For example, most countries in this sample
Table 3 Depositor guarantees and the fiscal and output costs of banking resolution in 33 systemic crises 1977–2002a Length of crisis (years), averageb
Non-performing loans (per cent of total loans), averagec
Bank credit/ Annual GDP (%), averaged
33
4.3
(2.7)
26.7
44.2
22 11 10 23
4.3 4.3 4.6 4.2
(2.7) (2.7) (2.2) (2.9)
29.3 17.3 23.7 28.2
16 7
3.9 4.9
(2.8) (3.1)
18
4.4
10 8 14
4.1 4.8 4.3
GNP per head (US$000s, PPP basis) at the start of the crisis, average
Cumulative fiscal costs of banking resolution (per cent of GDP), averagee
Output lossesf per cent of GDP (median in brackets)
6.6
15.0
13.3
(7.1)
47.8 37.0 44.9 43.9
7.9 4.0 7.3 6.3
16.6 11.8 7.8 17.4
14.8 10.1 6.2 16.1
(9.8) (5.0) (2.4)) (11.6)
29.7 19.5
46.9 37.1
7.5 3.6
19.4 12.8
17.6 12.7
(17.0) (4.8)
(2.8)
24.6
43.7
7.8
10.6
12.4
(6.7)
(2.7) (3.0) (2.5)
36.3 18.0 32.6
35.8 53.6 46.4
5.4 10.8 5.1
7.7 14.3 17.8
13.2 11.4 14.2
(5.4) (9.7) (6.5)
153
Source: Kyei (1995), Caprio and Klingebiel (2003), Hoelscher and Quintyn (2003), Honohan and Klingebiel (2003), World Bank database and IMF Financial Statistics various issues. a A systemic crisis is defined as when all, or nearly all, the capital in the banking system is eroded (see Caprio and Klingebiel, 2003). The crises are Finland (1991–93), Japan (1992-), Korea (1997–2000), Norway (1988–92), Spain (1977–85), Sweden (1991), Argentina (1980–82), Argentina (1995), Brazil (1994–96), Bulgaria (1996–97), Chile (1981–83), Colombia (1982–87), Cote dÕIvoire (1998–91), Czech Republic (1989–91), Ecuador (1996–2001 ), Ghana (1982–89), Hungary (1991–95), Indonesia (1997–), Malaysia (1997–2000), Mexico (1994–95), Paraguay (1995–99), Philippines (1981–87), Philippines (1998–2000), Poland (1992–95), Senegal (1988–91), Slovenia (1992–94), Sri Lanka (1989–93), Thailand (1983–87), Thailand (1997–2000), Turkey (1982–85), Turkey (2000–), Uruguay (1981–84), Venezuela (1994–95). b End of crisis based on qualitative expert judgment and in brackets when output growth returns to pre-crisis trend. c Estimated at peak. Data available for 19 countries only. Comparisons should be treated with caution since measures are dependent on country specific definition of non-performing loans and often non-performing loans are under recorded.
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All countries Blanket deposit guaranteeg • Yes • No Banking crisis alone Banking and currency crisish of which: • with blanket deposit guaranteeg • without blanket deposit guarantee Explicit ex ante deposit insurance • Yesi of which: Limitedi Unlimitedi • Noi
Number of crises
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Table 3 (continued) d At the beginning of the crisis period. Credit to the private sector from deposit money banks (IFS code 22d) as a share of annual nominal GDP (IFS code 99b). e Bank recapitalisation, government payouts to liability holders and public sector purchases of non-performing loans. f Output losses is the cumulative deviation in the growth of GDP during the crisis period from its pre crisis 10 year trend. Due to data limitations, a three and six year pre-crisis trend was used for Czech Republic and Slovenia respectively. Crisis ends when GDP growth returns to its pre-crisis trend or if not occurred estimated up until 2002. See Hoggarth and Saporta (2001). Data exclude Cote dÕIvoire. g Blanket guarantee is either explicit or where state banks account for 75% or more of banking system assets. h A currency crisis is defined, as in Frankel and Rose (1996), as a nominal depreciation in the domestic currency (against the US dollar) of 25% combined with a 10% increase in the rate of depreciation in any year of the banking crisis period. The latter condition is designed to exclude from currency crises high inflation countries with large trend rates of depreciation. i Countries with a limited coverage explicit deposit insurance scheme in place during the crisis were Spain (1977–85), Argentina (1995), Brazil (1994–96), Bulgaria (1996–97), Hungary (1991–95), Philippines (1981) and (1998–2000), Poland (1992–95), Sri Lanka (1989–93) and Venezuela (1994–95). Countries with an unlimited coverage scheme in place were Finland (1991–93), Japan (1992–), Korea (1997–2000), Norway (1988–92), Colombia (1982–87), Mexico (1994– 95), Turkey (1982–85) and (2000–). Countries without explicit insurance schemes in place during their banking crises were Sweden (1991), Chile (1981–83), Cote dÕIvoire (1988–91), Czech Republic (1989–91), Ecuador (1996–2001), Ghana (1982–89), Indonesia (1997), Malaysia (1997–2000), Paraguay (1995–99), Senegal(1988–91), Slovenia (1992–94), Thailand (1983–87), Thailand (1997–2000) and Uruguay (1981–84).
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that had in place a scheme with a limited coverage, in contrast to countries with an unlimited scheme or no scheme in place, did not resort to introducing a blanket government guarantee once a crisis broke out. However, in terms of the broader costs to the economy, there is (weak) evidence that countries which had in place limited (explicit) schemes witnessed larger output losses, everything else equal, than countries which had either unlimited schemes or no explicit schemes in place (see Table 2, equation (5)). Output losses are measured as the cumulative deviation in the growth of output during the crisis period from its pre-crisis ten year trend. Crisis is assumed to end when growth returns to its pre-crisis trend. 16 This seems to suggest that limited insurance schemes are less effective at limiting the damage to the banking system during a crisis than explicit unlimited schemes or de facto guarantees. With a limited scheme, depositors still have an incentive to run. However, as noted earlier, there is a tradeoff. Countries providing unlimited deposit protection (ex ante or de facto) will reduce the damage to the economy should a crisis occur (i.e. during the particular crisis) but have a greater likelihood of experiencing a crisis because of greater moral hazard. An additional point emphasised by Kaufman and Seelig (2002) is that during a crisis it is important for insured depositors (and other creditors) to have prompt access to the funds due to them. Delay in payment can reduce liquidity in the economy and encourage widespread bank runs. In many cases once a crisis has broken out, especially in countries without an explicit deposit insurance scheme in place or a scheme with unlimited coverage, blanket guarantees have been introduced for all creditors. In the recent crises in East Asia, Lindgren et al. (1999) found that the announcement of temporary blanket guarantees to all depositors and other creditors were successful in stopping runs by domestic deposits although not in securing rollover of foreign liabilities. De Luna-Martinez (2000) found not a single case of a depositor bank run during the Korean and Mexican crises once blanket guarantees were provided to depositors and other creditors (including external ones) and central bank liquidity was provided for a short period. More generally, Demirgu¨c¸-Kunt et al. (2000) found in a sample of 36 developed and emerging-country banking crises that at the outset of crises, deposits in the banking system as a whole did not decline. One interpretation of this is that blanket guarantees, which have usually been provided in systemic crises, have been successful in stopping banking system runs. But an alternative view is that broad guarantees were not needed, and depositors would in any case have simply shifted from perceived weak domestic banks to strong ones. The recent Indonesian situation appears to provide evidence for the first interpretation. In Indonesia it was only after the central bank shifted from a limited to a full guarantee that liquidity runs were stemmed but this may have reflected the inability of depositors to distinguish between weak and less weak banks. Goldstein (2000) believes that the limited deposit insurance scheme could have avoided a bank run had the 16
This result seems robust to different measures of the output losses incurred during banking crises. See Hoggarth and Saporta (2001) for a discussion of different estimates of output losses during banking crises. See also IMF (1998).
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public been convinced at the time that all, rather than just a few, of the insolvent banks in the system were being closed. This may again come down to the extent of disclosure on the banks in normal and crisis times. The more that is known about the risk profile of the banks the easier it would be to overcome information asymmetries in crises. Equation (3) in Table 2 shows a simple statistical relationship, controlling for other factors, between fiscal costs and government guarantees in a sample consisting only of systemic crises. Here too widespread deposit guarantees are positively associated, albeit weakly, with higher fiscal costs of crises. However, equation (6) in Table 2 suggests that there is no evidence, either positive or negative, of association between widespread deposit guarantees and the output losses incurred during crises. 17 Therefore, the introduction of widespread guarantees appears to increase the fiscal cost of crisis resolution without any clear-cut impact in reducing the broader output costs to the economy. Overall, countries with limited deposit protection schemes appear to experience higher output losses during a banking crises than countries with explicit or implicit unlimited schemes. But on the upside, the fiscal resolution costs are lower compared to when either an unlimited scheme or no scheme is in place. Unlimited schemes or no schemes result in many cases in the introduction of blanket insurance to all creditors once a crisis has broken out.
4. Conclusions These results show that countries face a tradeoff when designing safety nets for banking systems. Unlimited protection for depositors does appear to reduce the overall impact of a crisis on the economy. This result is true despite the fact that in our sample of banking crisis countries those that had unlimited schemes in place or no explicit schemes have much larger banking sectors than those with limited schemes. This is almost certainly because bank runs will be less when unlimited protection is provided and therefore harmful spillovers through either the effect on personal sector/corporate assets or credit are likely to be less. But there is a cost. The provision of an unlimited scheme, which is focussed on insulating the economy from some of the effects of a weak banking system, actually makes it more likely that the banking system will be weak and therefore will face a crisis. Another important result is that a decision to have in place no deposit protection arrangement, far from reducing moral hazard, actually seems to increase it relative to limited ex ante arrangements. This is because without an explicit pre-commitment to limit deposit protection, many countries in the throws of a crisis get pushed towards full government guarantees to limit the political and social cost. In this case a pre-commitment that there will be no protection whatsoever for depositors simply is not cred17 Although the regressions attempt to account for factors determining the size of the banking crisis shock there remains the possibility of causation running from the size of output losses to whether government guarantees are introduced or not as well as from government guarantees affecting the output losses during banking crises.
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ible. In terms of likelihood of crisis, countries with no scheme fair considerably better than those with an unlimited scheme but worse than those with a limited scheme.
Acknowledgment The views expressed in this paper are those of the authors and do not necessarily represent those of the Bank of England. The authors would like to thank an external referee for his comments. All errors and omissions are those of the authors.
Appendix A Table 4 gives an overview of the data for the safety net variables as well as the crisis dummy.
Table 4 Crisis and safety net variables Country
Crisis
Support
Explicit
No coins
Unlim
ARGENTINA AUSTRALIA AUSTRIA BELGIUM BRAZIL CANADA CHILE FINLAND FRANCE GERMANY INDONESIA IRELAND ISRAEL ITALY JAPAN REP. OF KOREA MALAYSIA NETHERLANDS NORWAY POLAND PORTUGAL SINGAPORE SPAIN SWEDEN SWITZERLAND THAILAND TURKEY UNITED KINGDOM USA
1 0 0 0 1 0 0 0 0 0 1 0 0 0 1 1 1 0 0 0 0 0 0 0 0 1 1 0 0
0 0.67 N/A N/A 0.44 1 0.8 1 0.6 0.6 0 0.67 0.67 0.25 0.9 0.7 0.5 0.67 1 0.11 0.5 1 0.31 1 1 0.33 0 0.35 0
1 0 1 1 1 1 1 1 1 1 0 1 0 1 1 1 0 1 1 1 1 0 1 1 1 0 1 1 1
1 0 0 1 1 1 0 1 1 0 0 0 0 1 1 1 0 1 1 0 0 0 1 1 1 0 1 0 1
0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 1 0 0
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References Barth, J.R., Caprio, G., Levine, R., 2002. Bank regulation and supervision: What works best? World Bank Working Paper. Baumann, U., Nier, E., 2003. Market discipline and financial stability. Bank of England Financial Stability Review, June. Bhattacharya, S., Jacklin, C., 1988. Distinguishing panics and information-based bank runs: Welfare and policy implications. Journal of Political Economy 96 (3). Caprio, G., Klingebiel, D., 2003. Episodes of systemic and borderline financial crises. World Bank database. De Luna-Martinez, J., 2000. Management and resolution of banking crises: Lessons from the Republic of Korea and Mexico. World Bank Discussion Paper no. 413. Demirgu¨c¸-Kunt, A., Detragiache, E., 2002. Does deposit insurance increase banking system stability? – An empirical investigation. Journal of Monetary Economics 49 (7), 1373–1406. Demirgu¨c¸-Kunt, A., Detragiache, E., Gupta, P., 2000. Inside the crisis: An empirical analysis of banking systems in distress. IMF Working Paper 156. Demirgu¨c¸-Kunt, A., Kane, E., 2002. Deposit insurance around the globe: Where does it work? Journal of Economic Perspectives 16 (2), 175–195. Demirgu¨c¸-Kunt, A., Sobaci, T., 2000. Deposit insurance around the world: A data base. World Bank Economic Review, 1513. Diamond, D., Dybvig, P., 1983. Bank runs, deposit insurance and liquidity. Journal of Political Economy 91 (3), 401–419. Dziobek, C., Pazarbasioglu, C., 1997. Lessons from systemic bank restructuring: A survey of 24 countries. IMF Working Paper no. 97/161. Eichengreen, B., Arteta, C., 2000. Banking crises in emerging markets: Presumptions and evidence. Working Paper No. 115, University of California, Berkeley. Garcia, G., 1999. Deposit insurance: A survey of actual and best practice. IMF Working Paper 99/54. Goldstein, M., 2000. IMF Structural Programs, presented at NBER Conference, October. Gropp, R., Vesala, J., 2001. Deposit insurance, moral hazard and market monitoring. ECB Working Paper No. 47. Hoelscher, D., Quintyn, M., 2003. Managing systemic banking crises. IMF Occasional Paper No. 224. Hoggarth, G., Saporta, V., 2001. Costs of banking system instability: Some empirical evidence. Bank of England Financial Stability Review, June. Honohan, P., 1997. Banking system failures in developing and transition countries: Diagnosis and prediction. BIS Working Paper No. 39. Honohan, P., Klingebiel, D., 2003. The fiscal cost implications of an accommodating approach to banking crisis. Journal of Banking and Finance 27, 1539–1560. Hovakimian, A., Kane, E.J., Laeven, L., 2003. How country and safety-net characteristics affect bank risk shifting. Journal of Financial Services Research 23, 177–204. International Monetary Fund, 1998. Financial crises: Characteristics and indicators of vulnerability. World Economic Outlook, Chapter 4, May. International Monetary Fund, 2002. Thailand, selected issues, July. Kane, E.J., 2000. Designing financial safety nets to fit country circumstances. World Bank, mimeo. Kane, E.J., Klingebiel, D., 2002. Alternatives to blanket guarantees for containing a systemic crisis. Mimeo. Kaufman, G., Seelig, S., 2002. Post-resolution treatment of depositors at failed banks: Implications for the severity of banking crises, systemic risk, and too big to fail. Economic Perspectives, 26. Kyei, A., 1995. Deposit protection arrangements: A survey. IMF Working Paper, no. 134. Lindgren, C.J., Balino, T., Enoch, C., Gulde, A., Quintyn, M., Teo, L., 1999. Financial sector crisis and restructuring – Lessons from Asia. IMF Occasional Paper no. 188. Merton, R.C., 1977. An analytical derivation of the cost of deposit insurance loan guarantees. Journal of Banking and Finance 1, 3–11.
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Mishkin, F.S., 1996. Understanding financial crises: A developing country perspective. NBER Working Paper No. 5600. OECD, 2002a. Experience with the resolution of weak financial institutions in the OECD area. Financial Market Trends, Chapter iv, No. 82, June. OECD 2002b. Turkey: Survey, October.
Banking crises and the design of safety nets Glenn Hoggarth, Patricia Jackson, Erlend Nier
*
Bank of England, Threadneedle Street, London EC2R 8AH, UK Available online 19 August 2004
Abstract Governments face conflicting objectives in terms of the provision and design of safety nets for banking systems. Safety nets may reduce market discipline and can thus increase the likelihood of a banking crisis. But safety nets are adopted because of the perceived benefits they will confer in either preventing a weak banking system from spilling over into a full-blown crisis or in enabling the government to handle a crisis more effectively. This paper provides evidence on the effects of government safety nets on both these aspects and discusses implications for policy. 2004 Elsevier B.V. All rights reserved. JEL Classification: G21; G28 Keywords: Deposit insurance; Banking crises
1. Introduction Governments face conflicting objectives in terms of the provision and design of safety nets for banking systems. They need to weigh the likely negative effects on market discipline and moral hazard against the possibly more positive effects that different features could have on the course of a crisis were one to develop. In this
*
Corresponding author. Tel.: +44207 6013239; fax: +44207 6013217. E-mail address: [email protected] (E. Nier).
0378-4266/$ - see front matter 2004 Elsevier B.V. All rights reserved. doi:10.1016/j.jbankfin.2004.06.019
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paper, we examine whether support arrangements influence the likelihood of banking crises and then look at the effect that they have on the costs of resolution. The negative effects of safety nets are well understood. A number of theoretical contributions have focussed on the effect of safety nets on shareholdersÕ incentives to take excessive risk. In the seminal study, Merton (1977) showed that flat rate deposit protection schemes create a subsidy that is more valuable if a bank engages in riskier activities. However, safety nets are adopted because of the perceived benefits they will confer in either preventing a weak banking system from spilling over into a full-blown crisis or in enabling the government to handle a crisis more effectively. The banking crises over the 1980s and 1990s led a large number of countries to rethink their safety net arrangements and consider for example introducing explicit deposit protection schemes (Garcia, 1999; Demirgu¨c¸-Kunt and Kane, 2002). An important policy issue therefore is what (if any) benefits stem from the particular features of safety nets. We first examine the effect of different types of safety nets on the likelihood of banking crises. Within that, we look at the implications of market expectations that the government will support debtholders and then at the effect of different deposit protection arrangements. As regards the latter, we distinguish between: (a) no explicit (but possibly an implicit) scheme; (b) an explicit scheme with limited coverage (and the effect of co-insurance where even within the limit the depositors do not receive 100% payout); (c) an explicit scheme with unlimited coverage. We find that an explicit unlimited deposit protection scheme increases the likelihood of banking crises. The next most likely group to have a crisis is that without any scheme ex ante, which might seem perverse. But most countries without an ex ante deposit protection scheme introduce blanket government guarantees during a crisis and this is therefore likely to be built into market expectations and to create moral hazard. The group least likely to experience a crisis is that with an explicit but limited deposit protection scheme, and within that group those countries that require depositors to co-insure. Pre-committing to providing only limited cover therefore appears effective in limiting moral hazard. We then examine the implications of different types of deposit protection arrangement for the resolution of crises, looking at fiscal cost and output losses. Here we find countries which offer explicit but unlimited schemes or no explicit scheme to have the highest fiscal costs of resolution – reflecting the use of widespread government guarantees during the crisis in these cases – but the lowest cost in terms of output forgone. From this a basic trade-off emerges. Countries with limited explicit schemes (and which therefore allow more losses to fall on depositors) suffer higher output losses than those countries which provide greater protection to depositors (either because of an explicit but unlimited scheme or de facto, through necessity, in the absence of an explicit scheme). But these countries are likely to gain in the longer term through the reduced likelihood of future crises.
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2. Safety nets and the likelihood of banking crises The effect of safety nets on the likelihood of systemic banking crises is ambiguous a priori. Safety nets may increase moral hazard and weaken market discipline, which should make banking crises more likely. On the other hand it is possible that this negative influence could be outweighed if safety nets make vulnerable systems less prone to full-blown crises, i.e. reduce the likelihood of a crisis becoming systemic. We distinguish between two aspects of government safety nets: deposit insurance and implicit government support for the banksÕ creditors. Theory suggests two opposing ways in which deposit insurance might affect the likelihood of banking crises. First, broad deposit insurance may reduce the likelihood of bank runs. This channel is suggested by models such as Diamond and Dybvig (1983), where bank runs may occur in a bad equilibrium in which depositors may lose their confidence in the banking system even if banks are fundamentally sound. But it extends to models where the likelihood of a bank run is higher the weaker is the bank in terms of fundamental solvency, such as Bhattacharya and Jacklin (1988), etc. On the other hand, the moral hazard incentives induced by deposit insurance might encourage banks to increase the risk of default. 1 When banks are subject to the threat of a bank run, they may behave more prudently than they would if that threat was removed by a comprehensive deposit insurance scheme. More generally, deposit insurance may reduce the link between a bankÕs risk of default and its funding cost, creating an incentive for the bank to increase default risk at the expense of depositors or the deposit insurance fund. 2 As in the case of explicit deposit insurance, implicit government support may have two opposing implications for bank stability. First, government support may prevent severe problems in a banking system from actually culminating in a crisis – in other words the support could disguise the extent of weakness in the banks. Governments typically extend implicit support to their banking system precisely because they want to prevent a systemic crisis. On the other hand, implicit government support may result in moral hazard incentives for banks who may be tempted to exploit the implicit subsidy provided by the government by increasing their risk. This may increase the probability of banking problems developing. A number of prior empirical studies examined the implications of deposit insurance on bank stability, e.g. Demirgu¨c¸-Kunt and Detragiache (2002), Eichengreen and Arteta (2000), Hovakimian et al. (2003), among others. The seminal study by Demirgu¨c¸-Kunt and Detragiache (2002) found, using a logit analysis, that the existence of deposit insurance increased the likelihood of crises, controlling for a number
1
Deposit insurance might also create moral hazard incentives for regulators. By reducing runs and liquidity problems at banks deposit insurarance may reduce pressure on regulators to resolve insolvencies promptly. 2 In principle, the funding charge adopted in deposit insurance schemes could be linked to a bankÕs relative riskiness. But in practice, this proves difficult, not least because banking risk is not easily observed or measured. As a result, the funding charge of the overwhelming majority of schemes is independent of a bankÕs riskiness, Demirgu¨c¸-Kunt and Kane (2002).
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of macro-variables. They also found that the adverse impact of deposit insurance on bank stability was stronger when the institutional environment was weak and that the impact of deposit insurance on bank stability tended to be stronger the more extensive was the coverage offered to depositors. Eichengreen and Areta (2000) used a different set of countries and a slightly different crisis definition. They found that, in contrast with the Demirgu¨c¸-Kunt and Detragiache (2002) finding, explicit deposit insurance decreased the likelihood of crises in their sample. 2.1. Empirical approach We use a data set 3 which covers 29 countries 4 over the years 1994–2001. According to Caprio and Klingebiel (2003), seven of these countries experienced a systemic banking crisis (defined as much or all of bank capital being exhausted) after 1993 – Korea, Thailand, Indonesia, Malaysia, Japan, Turkey and Argentina. In the case of the first four listed the onset of the crisis was in 1997/98. Turkey and Argentina experienced banking crisis that started in 2001 while JapanÕs crisis has been ongoing over the whole period. 5, 6 Using this dataset, we look at the extent to which the likelihood of a country experiencing a crisis after 1994 was affected by several aspects of the safety net in that country, controlling for initial macroeconomic conditions prevailing before the onset of the crisis. Demirgu¨c¸-Kunt and Sobaci (2000) provide a dataset on the existence and extent of deposit insurance schemes across countries. We use this to construct indices of the extent of depositor protection, focusing on those features that are likely to affect market discipline from depositors – co-insurance (i.e., less than 100% payout on the portion of deposits covered) and whether or not there is a limit on the pay-out receivable by depositors. In particular, we define explicit=1 if there exists an explicit deposit insurance scheme, =0 otherwise no co-insurance = 1 if there is an explicit scheme, specifying no co-insurance, =0 otherwise limited = 1 if there exists an explicit scheme, specifying no coverage limits, =0 otherwise.
3 The dataset is based on the bank-level dataset that was assembled by Baumann and Nier (2003) for a study of market discipline and bank risk-taking across countries. 4 These are Austria, Australia, Argentina, Belgium, Brazil, Canada, Chile, Finland, France, Germany, Indonesia, Ireland, Israel, Italy, Japan, Korea, Malaysia, the Netherlands, Norway, Poland, Portugal, Singapore, Spain, Sweden, Switzerland, Thailand, Turkey, the UK and the US. 5 The list of crisis countries includes Japan. This may raise questions regarding the endogeneity of the safety net variables. In particular, government support is measured at the end of the sample period. In Japan, measured government support is high, potentially due to the way the Japanese government responded to the crisis. In addition, unlimited deposit insurance was introduced only in 1996, arguably in response to the incipient crisis. On the other hand, anecdotal evidence suggests that, there had always been a presumption on the part of depositors and markets in Japan that banks would not be allowed to fail. All results are qualitatively unchanged if Japan is excluded from the list of crisis countries. 6 For the Nordic countries the onset of the crisis was before the start of the sample period.
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In addition to measuring explicit deposit insurance, we take account of the implicit support afforded to the banks by their government. The Fitch rating agency assigns a support rating that reflects the probability of support from a parent or the government. For most large, listed banks that were used to create the index for each country only the latter is important. The support rating ranges from 1 (near certain bail-out 7) to 5 (bail-out very unlikely). For each bank, Baumann and Nier (2003) constructed a measure of government support which takes the value 1 if the public support rating indicates that a bail-out is very likely (support rating equal to 1 or 2) and 0 if the public support rating indicates a low probability of a bail-out (rating is 3, 4, or 5). We use the country average of this variable as a measure of both the willingness and the ability (in fiscal terms) of the government in question to bail out its banks and their creditors and thus to prevent a systemic crisis. Probit regressions are then run on the following simple model of banking crises: crisis ¼ f ðSNet; ZÞ þ e;
ð1Þ
where ÔSNetÕ refers to aspects of the safety net and Z are control variables. Crisis is a country dummy variable that takes the value 1 if there has been a systemic banking crisis according to Caprio and Klingebiel (2003) and takes the value 0 otherwise. 8 Probit regressions recognise that crisis is defined as a zero-one event and are based on a model of the probability of banking crises. Table 4 in the Appendix gives an overview of the data for the safety net variables as well as the crisis dummy. The hypothesis we test using this regression model is whether safety net factors affect the likelihood of a banking crisis developing over the sample period, for given initial conditions (Z). 9 The list of variables that summarizes initial economic conditions includes the growth rate of GDP, the current account position in per cent of GDP, the short term interest rate, as well as per capita GDP, all as of 1994. A number of studies, e.g. Honohan (1997), have argued that crises often follow credit-driven booms, which are marked by high levels of GDP growth and large capital inflows. In addition, a number of studies document that crises tend to be preceded by high interest rates, e.g. Demirgu¨c¸-Kunt and Detragiache (2002). 10 Finally, Kane (2000) shows that across countries, measures of the strength of a countryÕs institutional environment–including the strength of its supervisory and regulatory regime – tend to increase with per capita GDP. 11
7
Fitch assumes that typically, shareholders will not be bailed out. The notion of support therefore refers to the likelihood of a creditor bail-out. 8 The resulting list of crisis countries is: Japan, Korea, Thailand, Indonesia, Malaysia, Turkey and Argentina. 9 This approach builds on Barth et al. (2002), who condition on the level of inflation prior to the crisis in cross-sectional probit regressions. 10 Mishkin (1996) argues that high interest rates were a factor contributing to the US savings and loans crises. But high interest rates may well also have played a role for some of the recent episodes of banking crises in emerging market economies, where policy interest rates were raised sharply to defend currency pegs. 11 See also Demirgu¨c¸-Kunt and Kane (2000).
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2.2. Results Table 1 summarises the main results. Note first that, while most macroeconomic control variables have a statistically weak effect on the likelihood of a banking crises developing, their signs appear plausible. In particular, a high growth of GDP and high capital inflows – associated with a current account deficit – tend to increase the likelihood of a crisis. High interest rates, likewise, tend to increase the likelihood of a crisis, while economic development, measured by per capita GDP tends to decrease it. As regards the safety net variables, it turns out that government support as measured by the average Fitch support rating for the banks in each country is statistically insignificant, but its negative sign suggests that the willingness and ability of Table 1 Impact of government safety nets on the likelihood of systemic banking crises Dep. variable: Crisis
Probit (1)
Support
0.9818 (0.3960)
Probit (2)
OLS (3)
Probit (4)
0.9611*** (0.0000)
Unlimited
2.2457** (0.0180)
Limited Limited with co-insurance Limited without co-insurance Implicit
GDP growth Current account Interest rate Constant
No. of obs Pseudo-R2 R-squared
OLS (6)
0.5159 (0.5930)
Explicit
GDP per cap
OLS (5)
0.0028 (0.9580) 1.5182 (0.9350) 0.0209 (0.1970) 0.0251 (0.6270) 0.5984 (0.7520)
0.0328 (0.5100) 5.1012 (0.7960) 0.014 (0.4140) 0.0141 (0.7960) 0.2002 (0.9340)
0.0078 (0.1620) 3.7920* (0.0630) 0.0026** (0.0500) 0.0001*** (0.0000) 0.1322 (0.4100)
27 0.3031
29 0.3071
29
P-values in parenthesis. * Statistical significance at the 10% level. ** Statistical significance at the 5% level. ***Statistical significance at the 1% level.
0.6525
0.0606 (0.2600) 13.2706 (0.5370) 0.0071 (0.5620) 0.0009 (0.6780) 2.0077 (0.3460) 29 0.572
0.9550*** (0.0000)
0.6865** (0.0280) 0.0068 (0.1780) 1.69 (0.3920) 0.0024 (0.1010) 0.0002*** (0.0000) 1.0995*** (0.0000)
1.0971*** (0.0000) 0.8558*** (0.0000) 0.7167** (0.0300) 0.0102* (0.0960) 1.8498 (0.3600) 0.0023* (0.0840) 0.0001*** (0.0030) 1.1550*** (0.0000)
29
29
0.6874
0.7248
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governments to bail out their banks may reduce the likelihood of a full-blown crisis, Table 1, Column 1. Also, the existence of an explicit deposit insurance scheme as such (as opposed to an implicit scheme) appears to have little effect on the incidence of a banking crisis, Column 2. If anything, the existence of a scheme appears to reduce the likelihood of a banking crisis, although this result is not statistically significant. This is in contrast with Demirgu¨c¸-Kunt and Detragiache (2002) who find in a sample of 61 countries between 1980 and 1997 that the existence of an explicit scheme increases the incidence of a banking crisis for countries that do not have an effective system of prudential regulation and supervision. However, like ours, their result is statistically weak and only just significant at the 10% level (with a P-value of 8%). 12 The reason for the conflicting results in different samples might be related to the fact that, on theoretical grounds the effect of an explicit scheme is ambiguous. On the one hand, an explicit scheme might reduce the likelihood of a depositor run, on the other hand an explicit scheme may remove the disciplining force of the threat of a run. Further, Gropp and Vesala (2001) argue that the introduction of an explicit scheme might even have beneficial incentive effects. Based on a European sample these authors show that the introduction of an explicit scheme may reduce moral hazard if deposit insurance credibly leaves out non-deposit creditors. This is because with a scheme in place governments may be more willing to let firms fail. To explore this argument in the context of our sample, we distinguish between explicit, but limited schemes and explicit unlimited schemes. Column 4 of Table 1 shows that countries with explicit, but limited schemes are far less likely to experience a crisis than are other countries in the sample, a result that is statistically significant at the 5% level. Column 3 of the same table suggests that countries with explicit unlimited schemes are more likely than other countries (including countries with no explicit schemes) to experience a banking crisis, where the result again is statistically strong. 13 This indicates that unlimited deposit protection schemes lead to less sound banking systems and that this outweighs any beneficial effects from the reduced incentives for depositors to run when the banking system is weak. The finding on unlimited schemes is in line with the result in Demirgu¨c¸-Kunt and Detragiache (2002) and underscores the moral hazard effects of this particular feature of the deposit insurance regime. Column 5 focuses on the effect of having no explicit (i.e. an implicit) scheme by introducing an additional dummy variables for such countries. Since a country either has no scheme, an explicit, but limited scheme, or an explicit and unlimited scheme, the latter category is omitted from the regression and all results are relative
12 Eichengreen and Areta (2000) examined the robustness of the Demirgu¨c¸-Kunt and Detragiache (2002) finding using a different set of countries and a slightly different crisis definition. Their results show a statistically negative coefficient, in contrast with the Demirgu¨c¸-Kunt and Detragiache (2002) finding. 13 In Columns 3, 5 and 6, inference is based on OLS rather than a probit regression. The reason is that convergence of the probit estimator was not achieved in these cases. The OLS regression applies a White correction for heteroskedasticity and P-values are based on robust standard errors. In addition, it turns out that for all models for which both estimators were feasible the results did not materially differ across estimation method.
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to that category. The regression suggests that, when compared to countries with an unlimited scheme, for countries with a limited scheme the likelihood of a banking crisis is reduced the most, but that countries with no (explicit) scheme are also less likely to experience a banking crisis than those countries with an explicit and unlimited scheme. Overall, this suggests a non-linear relationship as regards the effect of deposit insurance on the likelihood of crises. As compared to having no scheme, introducing an explicit scheme may well reduce the likelihood of a crisis. But the design of the scheme is important. Countries that offer unlimited protection are more likely to experience a crisis than countries that offer no explicit government support. The model presented in Table 1, Column 6 summarizes our results. It distinguishes between all three features – explicit versus implicit, limited versus unlimited as well as co-insurance versus no co-insurance – by introducing appropriate dummy variables. Again, the results are relative to the one omitted category, which is unlimited explicit insurance and they suggest the following ranking of the different possible regimes with respect to the likelihood of crisis. Countries with unlimited schemes are most likely to experience a crisis and those countries with no explicit scheme at all are significantly less likely to experience a crisis than this benchmark group. But the likelihood of a crisis is further reduced for those countries that have a limited depositor protection scheme. Among these countries, finally, the likelihood of crisis is the lowest for countries whose scheme includes a co-insurance element in addition to an absolute coverage limit.
3. The effect of safety nets on the costs of crises Although the evidence points to unlimited deposit protection schemes increasing the likelihood of crises, countries already vulnerable to a crisis may focus on the possible benefits in handling a crisis should it occur. Other countries might decide to remove any deposit protection arrangements in an attempt to maximise market discipline (e.g. New Zealand). A further important consideration is therefore the effect that various safety net arrangements may have on the ability of countries to manage and resolve a crisis and the resultant overall costs of crises. A number of recent empirical studies have assessed the impact of resolution techniques on the damage caused by crises. Dziobek and Pazarbasioglu (1997) find that most progress in restoring the banking systemÕs financial strength and its intermediation role occurs for countries that take action within one year of problems emerging. Kane and Klingebiel (2002) also emphasise that prompt intervention, especially where actions mimic market behaviour, minimises the damage caused by crises. Honohan and Klingebiel (2003) find in a sample of 40 developed country and emerging market crises that open-ended liquidity support and blanket guarantees increase the direct fiscal costs of crisis resolution. We consider the effect of ex ante arrangements such as limited and unlimited deposit protection schemes and expost measures introduced once a crisis has started such as government guarantees for depositors.
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The costs of banking crises are measured in two ways – a narrow measure based on estimates of the fiscal costs of crisis resolution and a broader measure proxied by the fall in output during the banking crisis period. Fiscal costs are the estimated net present value of the budgetary cost of the crisis based on official or expert assessment. These costs include both fiscal and quasi-fiscal outlays for financial restructuring including the recapitalization cost for banks, bailout costs related to covering depositors and creditors and debt relief schemes for bank borrowers. 14 These estimates may not be strictly comparable across countries. They may also overstate the final costs to the government to the extent they will receive future proceeds from re-privatisation and income from loan recoveries. Although Honohan and Klingebiel (2003) find that blanket government guarantees (and open-ended central bank liquidity support) are associated with higher fiscal costs of crisis resolution this does not imply necessarily causation. 15 Fiscal costs would be expected to be higher the larger the adverse shock to the banking system. But in face of such a potential systemic threat it is more likely that the authorities would also provide liquidity support and guarantees to liability holders. For example, full-blown systemic crises such as those in Japan, east Asia and in the Nordic countries would be expected to incur higher resolution costs together with government guarantees and LOLR, than smaller banking problems such as the US S&L crisis, Credit Lyonnais and the banking problems in Australia and New Zealand in the late 1980s. However, Honohan and Klingebiel include such episodes of banking problems as well as major crises in their sample. This suggests that comparisons of crisis intervention techniques and fiscal costs need to take account of the magnitude of the crisis. Second, even if intervention results in higher fiscal costs this needs to be weighed against the potential benefits to the wider economy from avoiding a systemic meltdown of the financial system. In the United StatesÕ banking crisis in the early 1930s the absence of depositor guarantees and liquidity support kept the fiscal costs low but at the expense of contributing to the marked decline in output at the time. Equations (1) and (2) in Table 2 show simple statistical relationships between fiscal costs and different ex ante insurance schemes in a sample of systemic crises – that is where the capital of the whole banking system was depleted or close to depletion. The amount of bank intermediation in the economy (measured by bank credit/GDP) and whether a currency crisis also occurred simultaneously are used as quantifiable proxies for the size of the banking crisis shock while GNP per head is used as a crude proxy for the ability of the financial system to withstand the shock. The results need to be treated with a degree of caution, because of the limited sample of crises (33) and the potential importance of country specific factors affecting the costs of crisis. Nonetheless, bearing these caveats in mind, controlling for other factors, it appears that countries that had in place an explicit scheme incurred lower fiscal 14
The data source is Honohan and Klingebiel (2003). Open-ended liquidity support is defined as liquidity support provided for more than 12 months which is greater than the aggregate capital of the banking system. Blanket guarantees are either explicit government guarantees or implicit ones proxied by where state banks account for more than 75% of the banking systemÕs assets. 15
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Table 2 Impact of explicit deposit insurance and government deposit guarantees on the fiscal costs (FCOSTS) and output losses (YLOSSES) of resolution in systemic banking crises Dependent variable
FCOSTS (1)
EXPLICIT DEPOSIT INSURANCE: UNLIMITED EXPLICIT DEPOSIT INSURANCE: LIMITED GOVERNMENT GUARANTEE CREDIT/GDP CURRENCY CRISIS GNP PER HEAD
R2 Number of observations
YLOSSES (2)
(3)
(4)
(5)
(6)
4.7 (0.32)
3.3 (0.56) 8.4* (0.07)
4.8 (0.22)
0.18** (0.04) 5.1 (0.28) 0.9 (0.11)
0.15* (0.07) 5.6 (0.21) 0.8* (0.09)
4.0 (0.22) 0.17** (0.05) 5.0 (0.29) 0.9* (0.09)
0.08 32
0.18 32
0.09 32
0.41*** (0.00) 9.5** (0.02) 0.5 (0.27)
0.43*** (0.00) 9.1** (0.03) 0.7* (0.10)
2.4 (0.56) 0.42*** (0.00) 8.8** (0.04) 0.8* (0.07)
0.60 31
0.60 31
0.58 31
Sources: World Bank database and Kyei (1995). FCOSTS: fiscal costs of resolution % of GDP. Sources: Caprio and Klingebiel (2003), Barth et al. (2002), IMF (2002), OECD (2002a,b). YLOSSES: cumulative deviation in the growth of GDP during the crisis period from its pre crisis 10 year trend. GOVERNMENT GUARANTEE: 1 where explicit blanket government guarantee or implicit one (where state banks account for 75% or more of banking system assets), 0 otherwise. Source: Honohan and Klingebiel (2003). CREDIT/GDP: Bank credit to the private sector/annual GDP (%). Source: IMF, International Financial Statistics. CURRENCY CRISIS: 1 where currency crisis, 0 otherwise. Currency crisis is a nominal depreciation (against the US dollar) of 25% combined with a 10% increase in the rate of depreciation in any year of the banking crisis period. Source: IMF, International Financial Statistics. GNP PER HEAD: GNP per head (US$000s, PPP) in the year that the banking crisis began. EXPLICIT DEPOSIT INSURANCE: 1 where an explicit deposit insurance scheme is in place before or during the crisis, 0 otherwise. UNLIMITED: 1 where an explicit but unlimited deposit insurance scheme is in place before or during the crisis, 0 otherwise. LIMITED: 1 where an explicit but limited deposit insurance scheme is in place before or during the crisis, 0 otherwise. P-values in parenthesis. * Statistical significance at the 10% level. ** Statistical significance at the 5% level. *** Statistical significance at the 1% level.
resolution costs than countries without an explicit scheme (see Table 3). However, this lower fiscal cost seems to be confined to schemes with a ceiling on the amount of deposits insured (Table 2, equation (2)) rather than schemes without a ceiling (equation (1)). This might imply that limited explicit schemes reduce the potential scope of bail out by making it clear ex ante which depositors would and would not be covered by the scheme in a crisis. For example, most countries in this sample
Table 3 Depositor guarantees and the fiscal and output costs of banking resolution in 33 systemic crises 1977–2002a Length of crisis (years), averageb
Non-performing loans (per cent of total loans), averagec
Bank credit/ Annual GDP (%), averaged
33
4.3
(2.7)
26.7
44.2
22 11 10 23
4.3 4.3 4.6 4.2
(2.7) (2.7) (2.2) (2.9)
29.3 17.3 23.7 28.2
16 7
3.9 4.9
(2.8) (3.1)
18
4.4
10 8 14
4.1 4.8 4.3
GNP per head (US$000s, PPP basis) at the start of the crisis, average
Cumulative fiscal costs of banking resolution (per cent of GDP), averagee
Output lossesf per cent of GDP (median in brackets)
6.6
15.0
13.3
(7.1)
47.8 37.0 44.9 43.9
7.9 4.0 7.3 6.3
16.6 11.8 7.8 17.4
14.8 10.1 6.2 16.1
(9.8) (5.0) (2.4)) (11.6)
29.7 19.5
46.9 37.1
7.5 3.6
19.4 12.8
17.6 12.7
(17.0) (4.8)
(2.8)
24.6
43.7
7.8
10.6
12.4
(6.7)
(2.7) (3.0) (2.5)
36.3 18.0 32.6
35.8 53.6 46.4
5.4 10.8 5.1
7.7 14.3 17.8
13.2 11.4 14.2
(5.4) (9.7) (6.5)
153
Source: Kyei (1995), Caprio and Klingebiel (2003), Hoelscher and Quintyn (2003), Honohan and Klingebiel (2003), World Bank database and IMF Financial Statistics various issues. a A systemic crisis is defined as when all, or nearly all, the capital in the banking system is eroded (see Caprio and Klingebiel, 2003). The crises are Finland (1991–93), Japan (1992-), Korea (1997–2000), Norway (1988–92), Spain (1977–85), Sweden (1991), Argentina (1980–82), Argentina (1995), Brazil (1994–96), Bulgaria (1996–97), Chile (1981–83), Colombia (1982–87), Cote dÕIvoire (1998–91), Czech Republic (1989–91), Ecuador (1996–2001 ), Ghana (1982–89), Hungary (1991–95), Indonesia (1997–), Malaysia (1997–2000), Mexico (1994–95), Paraguay (1995–99), Philippines (1981–87), Philippines (1998–2000), Poland (1992–95), Senegal (1988–91), Slovenia (1992–94), Sri Lanka (1989–93), Thailand (1983–87), Thailand (1997–2000), Turkey (1982–85), Turkey (2000–), Uruguay (1981–84), Venezuela (1994–95). b End of crisis based on qualitative expert judgment and in brackets when output growth returns to pre-crisis trend. c Estimated at peak. Data available for 19 countries only. Comparisons should be treated with caution since measures are dependent on country specific definition of non-performing loans and often non-performing loans are under recorded.
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All countries Blanket deposit guaranteeg • Yes • No Banking crisis alone Banking and currency crisish of which: • with blanket deposit guaranteeg • without blanket deposit guarantee Explicit ex ante deposit insurance • Yesi of which: Limitedi Unlimitedi • Noi
Number of crises
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Table 3 (continued) d At the beginning of the crisis period. Credit to the private sector from deposit money banks (IFS code 22d) as a share of annual nominal GDP (IFS code 99b). e Bank recapitalisation, government payouts to liability holders and public sector purchases of non-performing loans. f Output losses is the cumulative deviation in the growth of GDP during the crisis period from its pre crisis 10 year trend. Due to data limitations, a three and six year pre-crisis trend was used for Czech Republic and Slovenia respectively. Crisis ends when GDP growth returns to its pre-crisis trend or if not occurred estimated up until 2002. See Hoggarth and Saporta (2001). Data exclude Cote dÕIvoire. g Blanket guarantee is either explicit or where state banks account for 75% or more of banking system assets. h A currency crisis is defined, as in Frankel and Rose (1996), as a nominal depreciation in the domestic currency (against the US dollar) of 25% combined with a 10% increase in the rate of depreciation in any year of the banking crisis period. The latter condition is designed to exclude from currency crises high inflation countries with large trend rates of depreciation. i Countries with a limited coverage explicit deposit insurance scheme in place during the crisis were Spain (1977–85), Argentina (1995), Brazil (1994–96), Bulgaria (1996–97), Hungary (1991–95), Philippines (1981) and (1998–2000), Poland (1992–95), Sri Lanka (1989–93) and Venezuela (1994–95). Countries with an unlimited coverage scheme in place were Finland (1991–93), Japan (1992–), Korea (1997–2000), Norway (1988–92), Colombia (1982–87), Mexico (1994– 95), Turkey (1982–85) and (2000–). Countries without explicit insurance schemes in place during their banking crises were Sweden (1991), Chile (1981–83), Cote dÕIvoire (1988–91), Czech Republic (1989–91), Ecuador (1996–2001), Ghana (1982–89), Indonesia (1997), Malaysia (1997–2000), Paraguay (1995–99), Senegal(1988–91), Slovenia (1992–94), Thailand (1983–87), Thailand (1997–2000) and Uruguay (1981–84).
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that had in place a scheme with a limited coverage, in contrast to countries with an unlimited scheme or no scheme in place, did not resort to introducing a blanket government guarantee once a crisis broke out. However, in terms of the broader costs to the economy, there is (weak) evidence that countries which had in place limited (explicit) schemes witnessed larger output losses, everything else equal, than countries which had either unlimited schemes or no explicit schemes in place (see Table 2, equation (5)). Output losses are measured as the cumulative deviation in the growth of output during the crisis period from its pre-crisis ten year trend. Crisis is assumed to end when growth returns to its pre-crisis trend. 16 This seems to suggest that limited insurance schemes are less effective at limiting the damage to the banking system during a crisis than explicit unlimited schemes or de facto guarantees. With a limited scheme, depositors still have an incentive to run. However, as noted earlier, there is a tradeoff. Countries providing unlimited deposit protection (ex ante or de facto) will reduce the damage to the economy should a crisis occur (i.e. during the particular crisis) but have a greater likelihood of experiencing a crisis because of greater moral hazard. An additional point emphasised by Kaufman and Seelig (2002) is that during a crisis it is important for insured depositors (and other creditors) to have prompt access to the funds due to them. Delay in payment can reduce liquidity in the economy and encourage widespread bank runs. In many cases once a crisis has broken out, especially in countries without an explicit deposit insurance scheme in place or a scheme with unlimited coverage, blanket guarantees have been introduced for all creditors. In the recent crises in East Asia, Lindgren et al. (1999) found that the announcement of temporary blanket guarantees to all depositors and other creditors were successful in stopping runs by domestic deposits although not in securing rollover of foreign liabilities. De Luna-Martinez (2000) found not a single case of a depositor bank run during the Korean and Mexican crises once blanket guarantees were provided to depositors and other creditors (including external ones) and central bank liquidity was provided for a short period. More generally, Demirgu¨c¸-Kunt et al. (2000) found in a sample of 36 developed and emerging-country banking crises that at the outset of crises, deposits in the banking system as a whole did not decline. One interpretation of this is that blanket guarantees, which have usually been provided in systemic crises, have been successful in stopping banking system runs. But an alternative view is that broad guarantees were not needed, and depositors would in any case have simply shifted from perceived weak domestic banks to strong ones. The recent Indonesian situation appears to provide evidence for the first interpretation. In Indonesia it was only after the central bank shifted from a limited to a full guarantee that liquidity runs were stemmed but this may have reflected the inability of depositors to distinguish between weak and less weak banks. Goldstein (2000) believes that the limited deposit insurance scheme could have avoided a bank run had the 16
This result seems robust to different measures of the output losses incurred during banking crises. See Hoggarth and Saporta (2001) for a discussion of different estimates of output losses during banking crises. See also IMF (1998).
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public been convinced at the time that all, rather than just a few, of the insolvent banks in the system were being closed. This may again come down to the extent of disclosure on the banks in normal and crisis times. The more that is known about the risk profile of the banks the easier it would be to overcome information asymmetries in crises. Equation (3) in Table 2 shows a simple statistical relationship, controlling for other factors, between fiscal costs and government guarantees in a sample consisting only of systemic crises. Here too widespread deposit guarantees are positively associated, albeit weakly, with higher fiscal costs of crises. However, equation (6) in Table 2 suggests that there is no evidence, either positive or negative, of association between widespread deposit guarantees and the output losses incurred during crises. 17 Therefore, the introduction of widespread guarantees appears to increase the fiscal cost of crisis resolution without any clear-cut impact in reducing the broader output costs to the economy. Overall, countries with limited deposit protection schemes appear to experience higher output losses during a banking crises than countries with explicit or implicit unlimited schemes. But on the upside, the fiscal resolution costs are lower compared to when either an unlimited scheme or no scheme is in place. Unlimited schemes or no schemes result in many cases in the introduction of blanket insurance to all creditors once a crisis has broken out.
4. Conclusions These results show that countries face a tradeoff when designing safety nets for banking systems. Unlimited protection for depositors does appear to reduce the overall impact of a crisis on the economy. This result is true despite the fact that in our sample of banking crisis countries those that had unlimited schemes in place or no explicit schemes have much larger banking sectors than those with limited schemes. This is almost certainly because bank runs will be less when unlimited protection is provided and therefore harmful spillovers through either the effect on personal sector/corporate assets or credit are likely to be less. But there is a cost. The provision of an unlimited scheme, which is focussed on insulating the economy from some of the effects of a weak banking system, actually makes it more likely that the banking system will be weak and therefore will face a crisis. Another important result is that a decision to have in place no deposit protection arrangement, far from reducing moral hazard, actually seems to increase it relative to limited ex ante arrangements. This is because without an explicit pre-commitment to limit deposit protection, many countries in the throws of a crisis get pushed towards full government guarantees to limit the political and social cost. In this case a pre-commitment that there will be no protection whatsoever for depositors simply is not cred17 Although the regressions attempt to account for factors determining the size of the banking crisis shock there remains the possibility of causation running from the size of output losses to whether government guarantees are introduced or not as well as from government guarantees affecting the output losses during banking crises.
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ible. In terms of likelihood of crisis, countries with no scheme fair considerably better than those with an unlimited scheme but worse than those with a limited scheme.
Acknowledgment The views expressed in this paper are those of the authors and do not necessarily represent those of the Bank of England. The authors would like to thank an external referee for his comments. All errors and omissions are those of the authors.
Appendix A Table 4 gives an overview of the data for the safety net variables as well as the crisis dummy.
Table 4 Crisis and safety net variables Country
Crisis
Support
Explicit
No coins
Unlim
ARGENTINA AUSTRALIA AUSTRIA BELGIUM BRAZIL CANADA CHILE FINLAND FRANCE GERMANY INDONESIA IRELAND ISRAEL ITALY JAPAN REP. OF KOREA MALAYSIA NETHERLANDS NORWAY POLAND PORTUGAL SINGAPORE SPAIN SWEDEN SWITZERLAND THAILAND TURKEY UNITED KINGDOM USA
1 0 0 0 1 0 0 0 0 0 1 0 0 0 1 1 1 0 0 0 0 0 0 0 0 1 1 0 0
0 0.67 N/A N/A 0.44 1 0.8 1 0.6 0.6 0 0.67 0.67 0.25 0.9 0.7 0.5 0.67 1 0.11 0.5 1 0.31 1 1 0.33 0 0.35 0
1 0 1 1 1 1 1 1 1 1 0 1 0 1 1 1 0 1 1 1 1 0 1 1 1 0 1 1 1
1 0 0 1 1 1 0 1 1 0 0 0 0 1 1 1 0 1 1 0 0 0 1 1 1 0 1 0 1
0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 1 0 0
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