Working Paper Series

Market Discipline by Bank Creditors

during the 2008-2010 Crisis

Published as: “Market Discipline by Bank Creditors during the 2008-2010

Crisis”, Journal of Financial Stability 20, (2015): 51-69.

Rosalind L. Bennett

Federal Deposit Insurance Corporation

Vivian Hwa

Federal Deposit Insurance Corporation

Myron L. Kwast

Federal Deposit Insurance Corporation

First Version: March 2011

Current Version: March 2014

FDIC CFR WP 2014-03

fdic.gov/cfr

NOTE: Staff working papers are preliminary materials circulated to stimulate discussion and critical

comment. The analysis, conclusions, and opinions set forth here are those of the author(s) alone and do

not necessarily reflect the views of the Federal Deposit Insurance Corporation. References in publications

to this paper (other than acknowledgment) should be cleared with the author(s) to protect the tentative

character of these papers.
Market Discipline by Bank Creditors during the 2008-2010 Crisis*

Rosalind L. Bennett**

Division of Insurance and Research 

Federal Deposit Insurance Corporation 

Vivian Hwa 

Division of Insurance and Research 

Federal Deposit Insurance Corporation 

Myron L. Kwast 

Center for Financial Research 

Federal Deposit Insurance Corporation 

First Draft: March 2011 

Current Draft: August 2014

Abstract 

This paper shows that the liability classes most likely to exhibit evidence of market discipline during the 

recent financial crisis were uninsured depositors, insured depositors, and general creditors. We evaluate 

the FDIC’s expectations about losses to creditors at banks that failed between 2008 and 2010 to establish 

that these creditors expected to incur loss. Our empirical tests find evidence of quantity market discipline 

that tends to begin far enough in advance to signal to both banks and supervisors that corrective actions 

can and should be taken. Consistent with the literature, our results suggest that during the crisis, quantity 

discipline was relatively strong and price market discipline was relatively weak. Our findings support 

several policy implications for encouraging market discipline. 

JEL Classifications: G01, G21, G28, G33, H12 

Keywords: bank failures, financial crisis, market discipline 

Opinions expressed in this paper are those of the authors

and not necessarily those of the FDIC. 

*

 The authors thank Steve Burton, Rebel Cole, Stefan Jacewitz, Paul Kupiec, James Marino, Gail Patelunas, Jon 

Pogach, other colleagues at the FDIC, and seminar participants at the European Central Bank and the Norges Bank 

for extremely helpful comments and suggestions; and Jocelyn Grazal and Cody Hyman for outstanding research 

assistance. All errors are the authors’. 

** Corresponding author: Rosalind L. Bennett, FDIC, 550 17th St NW, Washington, DC 20429, Tel. 202-898-7160, 

e-mail: rbennett@fdic.gov 
1

Market Discipline by Bank Creditors during the 2008-2010 Crisis 

The recent financial crisis resulted in the failure of over 300 banks and thrifts from 2008 through 

2010 and most of these were community and medium-sized institutions. This paper examines these 

failures with two questions in mind. First, when a bank failed, what classes of creditors did the FDIC 

expect would incur losses and how large did the FDIC expect those losses to be? Second, is there 

evidence that in the months before failure, these creditors exerted either quantity or price market 

discipline on their banks? 

It is important to answer these questions because it is widely believed that the liability guarantees 

and direct capital injections used by the government during the crisis undermined market discipline.1

Creditors who believe that their funds are at risk either from outright loss or from a delay in access may 

actively monitor their banks and also take actions to protect themselves when the probability of their 

banks’ failure is perceived to be significant and/or increasing. Such actions may discipline a bank’s risk 

taking. For this reason alone, evidence of market discipline at banks that clearly will be allowed to fail 

would be of interest. But second and perhaps more important, a study of such evidence may yield 

valuable guidance on how best to encourage market discipline in the post-crisis world at banks of all 

sizes. Lastly, although it has long been known that in a bank failure the FDIC and bank stockholders 

should expect losses and that uninsured creditors could incur losses, the loss rates that the FDIC expected 

uninsured creditors to experience have not been known.2

 By documenting the loss rates expected by the 

1 For discussions of these guarantees and injections in the United States, see Bair (2009) and Bernanke (2009). In 

reaction to fears that market discipline had been undermined, a core mandate of the Dodd-Frank Wall Street Reform 

and Consumer Protection Act (Dodd-Frank Act), enacted in July 2010, is to promote market discipline. See, for 

example, Financial Stability Oversight Council (2011, p. 11). Berger and Turk-Ariss (2012) find evidence consistent 

with the view that in both the United States and the European Union government actions contributed to declines in 

depositor discipline during and after the crisis. 

2

 Stockholders are not considered further in this study because it is well known that they typically lose all of their 

claims. Indeed, according Bennett and Unal (2009), stockholders received payments in only 6 of the 1,213 BIF- and 

DIF-insured banks that failed between 1986 and 2007. 
2

FDIC, this paper will help bank creditors and other market participants better understand the extent to 

which uninsured bank liabilities are truly at risk, and overall financial market efficiency will improve. 

To address the questions, we first provide evidence that bank creditor classes were subject to risk 

of losses by evaluating data on the FDIC’s expectation of loss to each creditor class.3

 Then, we analyze 

the dynamics of the liability structure at banks during the crisis. We look at both failed banks, and those 

that did not fail. For the banks that did not fail, we group them by risk as indicated by their supervisory 

rating. This allows us to determine if there is evidence that market discipline is stronger at riskier banks. 

We also analyze the spread between uninsured and insured deposits to evaluate price discipline at banks 

during the crisis. 

We find that in almost all failures during the recent crisis the FDIC expected itself and general 

creditors to incur substantial losses. In a significant but much smaller number of failures, the FDIC 

expected uninsured depositors to take large losses because the FDIC typically chose a resolution method 

in which an acquiring bank assumed all uninsured deposits of the failed bank during the crisis. Still, it is 

clear that, ex ante, uninsured depositors were not assured of full recovery and therefore faced significant 

uncertainty as to the security of their funds. The FDIC did not expect secured creditors to incur losses, 

although secured claims were typically a substantial percentage of total claims. In the banks where 

subordinated debt existed, the FDIC expected holders of such debt to lose 100 percent of their claims. 

However, very few banks that failed held subordinated debt and when they did it was a small amount. 

Furthermore, our statistical tests support the view that subordinated debt was not a relevant source of 

market discipline at the failed banks used in this study. Overall, the liability categories most likely to 

exhibit evidence of market discipline were the uninsured deposits, insured deposits, and general creditor 

claims. 

Our results indicate that changes in liability shares before a bank’s failure are consistent with 

quantity market discipline (QD) in which liability holders reallocate their portfolios in ways that protect 

3

 The FDIC covers insured deposits in full and then stands in their place in the priority of claims. No insured 

depositor loses money, however the FDIC will lose money on the insured deposit claim. 
3

them from losses. We call these changes “QD-consistent portfolio reallocations”. These reallocations 

include the following actions: creditors convert their funds to insured claims at their current bank; they 

move their funds to banks they perceive as relatively safe; and, in the case of general creditors, they 

reduce their exposure to the bank. All of these actions have the potential both to constrain the ability of a 

bank to take risk and to signal to supervisors and market participants that the bank is becoming more 

risky. However, like most other researchers, we find evidence only of “monitoring” by creditors, not of 

“influencing” a bank’s risk taking. 

Importantly, our results indicate that during the crisis, QD-consistent portfolio reallocations 

typically began well before—often four or more quarters before—a bank failed. In addition, when we 

expand our analysis to include risky banks that did not fail, we observe comparable reallocations. Indeed, 

our expanded analysis finds that creditors generally seemed able to distinguish between very risky and 

safe banks. However, they appeared to have trouble assessing the risk of moderately risky banks and 

tended to treat them more like very risky banks. 

Our results for price market discipline (PD) are much less compelling than those for quantity 

discipline. On the one hand, we find weak evidence of price discipline. For example, average interest rate 

spreads between uninsured and insured deposits are positive. On the other hand, these spreads are not 

related to bank risk, and it is not clear whether our results reflect primarily the extent of PD or the 

inherent weaknesses of available data. Still, our findings of relatively strong QD and relatively weak PD 

during a crisis are consistent with expectations based on the existing literature. 

Our study both builds on and has several advantages over previous work. The first advantage is 

that, to our knowledge, no other study examines market discipline of any type at community and mediumsized banks during the recent crisis.4

 These banks are of particular interest because it is clear that they are 

4 Although Berger and Turk-Ariss (2012) examine depositor discipline during the crisis, their sample of U.S. banks 

is weighted heavily toward much larger banks than those in our sample. In addition, there is a growing literature on 

quantity discipline runs on large banks and “shadow banks” during the crisis, but this literature focuses on such 

nontraditional quantities as asset-backed commercial paper, repurchase agreements, and money market mutual fund 

shares. See, for example, Gorton (2008) and Bernanke (2010). 
4

at risk to fail. Second, no other study has identified the loss rates expected by the FDIC on the full range 

of failed-bank liability categories: FDIC claims, uninsured deposits, general creditor claims,5

 secured 

claims, and subordinated debt. Finally, to our knowledge no other study of failed banks has constructed 

comparison samples of nonfailed banks using broad supervisory measures of overall bank risk. 

The paper proceeds as follows. The next section—Section I—defines quantity and price market 

discipline and briefly reviews the literature on market discipline in banking, placing our paper within that 

literature. Section II describes the study’s 318 bank failures across several important dimensions—time, 

geographic region, size, and failed-bank resolution method. Section III documents loss rates expected by 

the FDIC in bank failures for the five classes of bank claims listed above (the FDIC claim; uninsured 

deposits; general creditor claims; secured claims; and subordinated debt). Section IV investigates the 

behavior of claims in these categories for evidence of quantity market discipline in the two years before a 

bank’s failure, and we compare this behavior with that of the same liability classes in risk-stratified 

samples of banks that did not fail. The investigation is preceded by an explanation of our empirical 

strategy and of the procedures we used. In Section V we briefly examine price discipline. The concluding 

section summarizes our results and discusses their policy implications. Appendix A is a chart defining 

receivership claims, and appendix B consists of three tables presenting the full regression results for the 

claim categories that are of primary interest.

I. Definition of Market Discipline and Literature Review 

When liability holders are exposed to the risk of loss and/or to the risk of delayed access to their 

funds, they may attempt to impose ex ante market discipline on their depository institutions. The goals of 

such market discipline are both to compensate creditors for the risks that banks take and to deter banks 

from taking excessive risks. The pre-crisis literature found reasonably strong evidence of market 

5

 General creditor claims include claims of outside law firms, accountants, information technology providers, 

landlords, and any other firm that was not paid for goods or services provided before the bank failed. (General 

creditor claims also include trading liabilities and foreign deposits, but for reasons given in note 25, they are not 

important for our purposes.) 
5

discipline at depository institutions. However, the estimated strength of market discipline depends on the 

extent to which the bank closure regime imposes losses on the uninsured and unsecured creditors.6

The pre-crisis literature considers market discipline as either a quantity or price mechanism which 

can be direct or indirect.7

 Direct quantity market discipline occurs when, ceteris paribus, a bank 

experiences withdrawals of funds as its risk increases. Withdrawals can be gradual or may become a run 

on the bank. Such discipline imposes a direct cost on a banking organization that chooses to increase its 

risk. Indirect quantity discipline occurs when bank creditors restructure their holdings in ways that signal 

they are concerned about a bank’s safety and, as a result of this signal, supervisors or private agents 

require the bank to take risk-reducing actions. Whether direct or indirect, we call such movements in 

deposits “QD-consistent portfolio reallocations,” and they can include moving funds to a bank they 

perceive to be safer, converting uninsured funds to insured funds, obtaining collateral, and cancelling 

existing banking relationships.

Direct price market discipline occurs when, ceteris paribus, a bank must pay higher risk 

premiums on at-risk liabilities (e.g., uninsured deposits) or suffer other risk-based cost increases (e.g., 

higher credit default swap spreads) as its risk increases. Indirect price discipline occurs when government 

supervisors or private agents monitor market prices and react to changes in those prices in ways that deter 

a bank from taking excessive risk. Bank supervisors might, for example, conduct a special examination or 

limit a bank’s activities in response to a large increase in the bank’s market risk premiums. 

6 Papers that emphasize the importance of the regulatory regime include Balasubramnian and Cyree (2011), 

Ashcraft (2008), Nier and Baumann (2006), Covitz et al. (2004), Goldberg and Hudgins (2002), and Jordan (2000). 

7 The distinction between quantity and price mechanisms is made by Park and Peristiani (1998), among others, and 

direct and indirect effects are discussed in Board of Governors (1999). Papers that focus on quantity discipline are 

discussed in the text. Papers that focus on price discipline include Balasubramnian and Cyree (2011), Curry et al. 

(2008), Goyal (2005), Krishnan et al. (2005), Bliss and Flannery (2002), Hancock and Kwast (2001), Board of 

Governors (1999), and Hannan and Hanweck (1988). Papers that focus on both quantity and price discipline include 

Berger and Turk-Ariss (2012), Schaeck (2008), Davenport and McDill (2006), Maechler and McDill (2006), Covitz 

et al. (2004), and Jagtiani and Lemieux (2001).Market discipline has been studied in an international context by 

Berger and Turk-Ariss (2012, 2010), Pop (2009), Murata and Hori (2006), Nier and Baumann (2006), and Peria and 

Schmukler (2001). A comprehensive discussion of the importance of bank liability structure can be found in Bradley 

and Shibut (2006). 
6

The literature suggests that at relatively low levels of bank risk, price discipline tends to 

dominate.8

 Consistent with this view, Ben-David, Palvia, and Spatt (2011) find that in the pre-crisis 

period (2007–2008), banks with low capital paid relatively higher CD rates than banks with higher capital 

(i.e., price discipline was operative). They also found that “as the crisis evolved, small low capital banks 

offered significantly lower CD rates, and large low capital banks offered the same CD rates as bettercapitalized banks.”9

 These results suggest that because our analysis is limited to a time of extremely high 

bank-specific and systemic risk, we may also expect to observe relatively low levels of PD. 

In contrast, the literature suggests that as tangible signs of serious weakness begin to appear, QD 

becomes more likely. In the banking literature, one of the most commonly used signals of QD is a 

decrease in the share of uninsured deposits in a bank’s liabilities. In addition, as the perceived risk of a 

bank’s failure rises significantly, withdrawals can become destabilizing and may lead to contagious runs 

on other banks. However, it is noteworthy that the pre-crisis literature on bank runs and contagion 

generally concluded that even these phenomena tended to “be bank-specific and rational.”10 Moreover, 

federal deposit insurance has virtually eliminated destabilizing runs.11 Because our analysis focuses on a 

high-risk period and the literature has found that QD dominates in these environments, we focus our 

search for evidence of market discipline on tests for QD-consistent portfolio reallocations. 

Previous literature has focused on an additional aspect of market discipline—monitoring versus 

influence. Bliss and Flannery (2002), emphasize the importance of distinguishing between the ability of 

bank owners and creditors to “monitor” accurately the financial condition of a firm and their ability to 

“influence” a bank’s risk-taking behavior. The authors point out that most studies of market discipline test 

8 For example, Maechler and McDill (2006) examined uninsured deposits and studied price and quantity discipline 

at both banks and thrifts from 1987 to 2000. They found “that good banks can raise uninsured deposits by raising 

their price, while weak banks cannot” (p. 1871). 

9

 Ben-David, Palvia, and Spatt (2011, p. 4). 

10 Kaufman (1994, p. 143). See also Calomiris and Mason (1997). 

11 And, according to a recent study of Russian banks by Karas et al. (2013), has blunted market discipline. 
7

only for monitoring, and our study is similarly constrained. They found little evidence that either bank 

stockholders or bond holders exert much influence. More generally, banks subject to monitoring by 

creditors most often do not fail, which implies that such creditors exert some influence. However, the 

effect of influence has proved hard to quantify.12

The previous studies most closely related to ours are Billett et al. (1998), Park and Peristiani 

(1998), Jordan (2000), Goldberg and Hudgins (2002, 1996), Maechler and McDill (2006), and Acharya 

and Mora (2011). A standard approach in these studies is to examine movements in some measure’s share 

of liabilities—for example, uninsured deposits’ share of total liabilities. Billett et al. found that as a 

bank’s risk increases, the percentage of insured deposits relative to total liabilities tends to increase as 

well. The authors interpreted this result as suggesting that market discipline was dampened by bank 

behavior. However, their analysis did not examine uninsured deposits, did not consider possible indirect 

market discipline, and examined only publicly traded banks. Building on Billett et al. (1998), Jordan 

(2000) examined flows of both uninsured and insured deposits at New England banks and thrifts that 

failed between 1989 and 1995. In addition, using data on the average cost of deposits, he looked for 

evidence that both uninsured and insured depositors demanded higher interest rates at riskier banks. 

Jordan found some evidence for both quantity and price discipline, sometimes beginning as much as two 

years before failure. He also discovered that at least some failed banks had been able to replace runoffs of 

uninsured deposits with insured deposits. 

In a quantity and price discipline study of thrifts from 1987 to 1991, Park and Peristiani (1998) 

found evidence of both QD and PD by uninsured depositors as well as weaker evidence for both types of 

discipline by insured depositors, but did not examine either banks or other classes of claims. Similarly, 

12 Maechler and McDill (2006) conclude that “depositor discipline not only raises the cost of choosing a higher 

level of risk but also may, at very high levels of risk effectively constrain bank managers’ behavior.” (p. 1871). 

Covitz et al. (2004) find that a bank holding company’s decision to issue subordinated debt is inversely related to the 

firm’s risk, an effect that could constrain a firm’s risk taking. Ashcraft (2008) finds that subordinated debt appears to 

reduce bank risk taking.
8

Goldberg and Hudgins (2002), studying thrifts for the period 1984 through 1994, found both that the ratio 

of uninsured deposits to total deposits declined as a thrift institution approached failure and that failing 

thrifts had a lower ratio of uninsured deposits before failure than did healthier thrifts. They interpreted 

their results as being consistent with quantity market discipline.13 Maechler and McDill (2006) examined 

uninsured deposits, but not other categories of claims, at both banks and thrifts from 1987 to 2000. 

Acharya and Mora (2011) were not concerned with market discipline per se but examined bank 

deposit rates and flows through the first quarter of 2009 to assess the extent to which banks functioned as 

liquidity providers. They found that banks “that are about to fail experienced increasingly large deposit 

outflows and reacted by raising deposit rates in an effort to stem the loss” (p. 19). 

II. Banks That Failed: Time, Region, Size, and Type of Resolution 

This section examines the 318 bank failures that occurred from 2008 through 2010 along four 

dimensions: time (quarter of failure), region of the country, asset size, and method of resolution. 14

Method of resolution receives particular attention. 

Table 1 shows the distribution of the 318 failures across each of the quarters in our sample and 

across five geographic regions.15 As shown in column 6, the number of failures increased substantially 

toward the end of 2008, when the broader financial crisis was at its worst. Indeed, only four banks failed 

early in the crisis—two in each of the first two quarters of 2008. The number of failures peaked in the 

13 Our empirical methodology for testing for QD is somewhat similar to that of Goldberg and Hudgins (2002). In a 

previous paper (1996), these authors examined shares of uninsured deposits at failing thrift institutions over a shorter 

period using a different methodology and found evidence of QD. 

14 There were 322 bank failures, excluding assistance transactions, between 2008 and 2010. Our analysis includes 

all but 4 of those failures. We exclude Washington Mutual Bank (WaMu), which closed on September 25, 2008, 

because it’s size (over $300 billion in total assets) and complexity make it such an extraordinarily special case that it 

would be misleading to compare it with the other banks in this study. We also exclude 3 banks that failed that were 

located in Puerto Rico. 

15 We use the location of a bank’s headquarters office to identify its primary state of operation, and then classify 

states into regions. For the specific states in a given region, see the notes to table 1. 
9

third quarter of 2009 and remained elevated through 2010.16 As for region, while bank failures occurred 

across all five regions and in 39 states, failures were concentrated in the South, Midwest, and West. These 

facts about quarter of failure and region suggest that our empirical analysis of market discipline will need 

to consider the time pattern of bank failures and include some control for geography. 

Table 2 displays the number of failures by asset size class and type of resolution. The failed banks 

range in size from about $5 million in total assets to about $35 billion.17 It should be emphasized that 

there are no money-center or internationally active banks in our sample. Although such banks received 

government assistance during the crisis, all were resolved in ways that did not require data about expected 

losses—the data used in this study. The asset size classes reflect the conventional definition of a 

community bank (total assets less than $1 billion). We also classify banks into size classes of $1 billion to 

$10 billion and over $10 billion in assets. As for resolution method, from 2008 through 2010 the FDIC 

used four methods for resolving failed banks: three types of purchase and assumption transactions and a 

deposit payout.18 It is important to understand how these methods function because the expected losses of 

key groups of uninsured creditors vary across resolution methods. 

16 The number of bank failures fell from 154 in 2010 to 92 in 2011 and 51 in 2012. Partly for this reason, we end our 

crisis period in 2010. 

17 The smallest bank in our sample held $6.2 million in assets at its failure date; the largest held $30.7 billion. In the 

five years before failure, the smallest amount of assets a sample failed bank ever had was around $4.4 million 

(merger adjusted) and the largest amount was around $33.5 billion (merger adjusted). 

18 As explained in the next section, usually the FDIC must resolve a failed bank in a way that is least costly to the 

Deposit Insurance Fund. Meeting this “least-cost test” requires calculating the expected loss. The major exception to 

the least-cost test requirement is the Federal Deposit Insurance Act’s so-called systemic risk exception that was in 

effect during our sample period. Under this exception, the FDIC could use another resolution method if the 

Secretary of the Treasury, in consultation with the President and with the written recommendation of two-thirds of 

the Federal Reserve Board and two-thirds of the FDIC Board, determined that use of the least-cost resolution would 

have serious adverse effects on economic conditions or financial stability and that use of an alternative method can 

mitigate these adverse effects. For more on the systemic risk exception, see Government Accountability Office 

(2010). For a fuller explanation of FDIC resolution methods, see Federal Deposit Insurance Corporation (1998b). 
10

Under the purchase and assumption types of resolution, the acquiring bank generally assumes all 

deposits (insured and uninsured) of the failed bank, some other liabilities, and some or all of the assets.19

In addition, the FDIC frequently entered into a “loss sharing” agreement with the acquiring bank under 

which the FDIC agreed to assume a portion of the losses on the assets that were purchased by the 

acquirer. Thus, in table 2 we distinguish between purchase and assumption transactions with a losssharing agreement (PAL) and purchase and assumption transactions without a loss-sharing agreement 

(PA). For the present study, however, the key point is that in PAL and PA resolutions, insured and 

typically all uninsured deposits were fully protected.20

A third type of purchase and assumption is an insured-only resolution (PI)—a type of purchase 

and assumption in which the acquiring bank assumes only insured deposits on the liabilities side and may 

also assume some or all assets. Importantly, in a PI transaction, uninsured depositors may incur losses and 

will almost surely have delayed access to their funds, as the FDIC sells the failed bank’s assets over 

time.21

In a deposit payout (PO) transaction, the FDIC pays depositors directly up to insurance limits, 

and puts all the assets into an FDIC receivership for liquidation. A deposit payout can be (1) a straight 

payoff of insured deposits by the FDIC, (2) an insured deposit transfer whereby a healthy depository 

agrees to act as the FDIC’s agent, or (3) the transfer of insured transaction accounts to a newly chartered 

deposit insurance national bank (DINB), with the time and savings deposits paid by the use of normal 

payout practices and transaction accounts wound down. The usual life of a DINB is between 30 and 60 

days. In all deposit payout cases, deposits over the insurance limit are not guaranteed. Furthermore, since 

19 Samolyk etal (2011) point out that the October 2008 increase in deposit insurance coverage from $100,000 to 

$250,000 probably increased acquirers’ willingness to assume all deposits, a hypothesis that is supported by their 

data. Another recent paper that examines bank failures during the crisis is Cole and White (2012). 

20 In some purchase and assumption transactions, “certain brokered deposits” (see 

www.fdic.gov/bank/historical/bank) were not purchased by the acquiring institution. If those brokered deposits had 

been uninsured, they could have been at risk of loss. 

21 One failure was resolved by the use of a PI resolution that also involved a loss-sharing agreement. We included 

this failure in the PI group. 
11

there is no acquiring bank, the FDIC as receiver must liquidate all of the failed bank’s assets. Uninsured 

depositors and other creditors receive payments from the proceeds as the assets are liquidated in 

accordance with the priority of their claims on the bank.22 In both PO and PI resolutions there is typically 

substantial uncertainty about the timing and amount of such payments. 

As shown in table 2, during the crisis the PAL was the most common resolution type (69 percent 

of failures).23 Overall, a PAL or PA resolution was used in 92 percent of the community bank cases and in 

84 percent of the medium-sized banks. In addition, 84 percent of the failures met the standard definition 

of a community bank, 14 percent were in the middle size class, and 2 percent (7 failures) were in our 

sample’s largest size class. Thus, the vast majority of our failed-bank sample is quite homogeneous with 

respect to size, and there does not appear to be a strong relationship between bank size and resolution 

method.24 Despite the severity of the financial crisis and policymakers’ preference during this period for 

maintaining macrofinancial stability, slightly over 9 percent of the failures (29 banks) were resolved using 

either the PI or the PO approach, both of which always put uninsured depositors at risk of loss. 

III. Expected Loss Rates by Claim Category

As indicated in the previous section, when a bank fails the FDIC must usually resolve it in a 

manner that is least costly to the deposit insurance fund (DIF). To help the FDIC Board determine which 

resolution method to use, FDIC staff prepares estimates of the cost of each of the resolution methods 

under consideration. FDIC staff estimate the expected losses not only to the DIF (which assumes all the 

22 There is no uncertainty about the priority ranking of claim payments: (1) administrative expenses of the FDIC, 

and secured claims to the extent that these claims are covered by collateral; (2) domestic deposits (including FDIC 

claims which result from paying insured depositors in full); (3) other general creditor claims or senior liabilities, 

including foreign deposits; (4) subordinated debt; and (5) at the end of the line are shareholder claims. 

23 The use of loss sharing was more prevalent in this financial crisis than in the previous one from 1980 to 1994.

The FDIC first used loss sharing in 1991. Between 1991 and 1993, the FDIC entered into loss share agreements with 

fewer than 10 percent of the banks that failed. These banks accounted for 40 percent of the assets in all the failed 

banks in those three years. In our sample, the FDIC entered into loss-sharing agreements in 69 percent of the 

failures—banks that accounted for 83.4 percent of the assets in the failed banks in our sample. See Federal Deposit 

Insurance Corporation (1998a). In addition, use of the PAL resolution type increased from 8 percent of sample 

failures in 2008 to 64 percent in 2009 and to 82 percent in 2010. 

24 Still, our empirical tests control for bank size (see Section IV). 
12

claims of insured depositors) but also to the four categories of uninsured claims: uninsured deposits, 

general creditor claims, secured liabilities, and subordinated debt.25

Before a bank fails and the FDIC announces the resolution method it will use, the holders of 

claims in the four uninsured categories are uncertain about the losses they could experience on their 

claims if the bank were to fail. The first reason for their uncertainty is that they cannot know which 

resolution method the FDIC would choose. The second reason is that unless their claims were to be 

assumed fully by an acquiring institution, uninsured depositors, general creditors, and subordinated debt 

holders would experience substantial uncertainty about both the size and the speed of recovery of their 

claims. With respect to the size of dollar loss, the loss rates expected by the FDIC are not made public. 

Moreover, the final amount of loss would not be known until the failed bank was fully resolved, which 

typically occurs after several years.26 With respect to timing, publicly available FDIC data indicate that in 

recent years uninsured claimants typically received around half of their claim within one and a half years 

of a bank’s failure. However, a claimant may receive his or her last payment anytime between one quarter 

and more than two and half years after failure. In addition, the percentage of claims payments in a given 

quarter may range between zero and 100 percent.27

25 These five claim categories (insured deposits and the four uninsured categories) sum to total liabilities. As 

mentioned in note 5, general creditor claims include not only the claims of outside law firms, accountants, 

information technology providers, landlords, and any other firm that was not paid for goods or services provided 

before the bank failed, but also trading liabilities and foreign deposits. Although these latter two types of account are 

potential sources of QD, it is very unusual for banks in our sample to hold them. For example, of the 85,926 bankquarters in our sample, trading liabilities and foreign deposits each appear only 0.6 percent of the time. Thus, we do 

not consider them important sources of potential QD for our sample. 

26 For this reason we are limited to using the FDIC’s expected loss rates. Although such estimates are clearly subject 

to revision, they are the best data available. 

27 Although the FDIC does not publicly disclose expected loss rates for any claimant other than itself and equity 

holders (always expected to lose 100 percent of their claim), it does provide a substantial amount of other 

information to the public about a bank failure. For more on these procedures, see Federal Deposit Insurance 

Corporation (1998b). 
13

We hand collect data from the Least Cost Test that was performed for the 318 failed banks in our 

sample. Table 3 displays expected loss rates for each liability category and each type of resolution.28 As 

shown in panel A, on average the FDIC expected to lose 28 percent of its total claim. The expected loss 

rates for uninsured deposits in PI and PO resolutions were quite high—on average, in a PI approximately 

28 percent and in a PO about 38 percent.29 Expected loss rates for general creditor claims (GCC) were

between 94 and 100 percent. Columns 4 and 5 show that subordinated debt holders were always expected 

to lose all of their claims and that secured creditors were always expected to fully recover their assets. 

As shown in panel B, insured deposits were present in all 318 failures; therefore the FDIC had 

claims in all failures. General creditor and secured claimants were also present in virtually all failures. 

However, uninsured depositors faced possible losses in only 25 bank failures (8 percent), and 

subordinated debt holders were present in only 23 failures (7 percent). 

As shown in panel C, FDIC claims are typically the largest claims with an average (at failure) of 

approximately 90 percent of total claims. Secured claims are typically the second largest set of claims (10 

percent), followed by uninsured deposits (2 percent). Both general creditors and subordinated debt 

holders (when present) are usually only about 1 percent of total claims. 

On balance, these results suggest that the most likely categories of claims to test for evidence of 

market discipline are uninsured deposits, insured deposits, and general creditors. As noted above, the 

previous literature has examined insured deposit shares and sometimes uninsured deposit shares. To our 

knowledge no previous study has considered general creditor claims as a potentially important source of 

market discipline. 

28 Unreported results from multivariate regressions that control for resolution type, bank size, region, and holding 

company status reinforce the univariate tests reported in the text, with one exception: expected loss rates of general 

creditor claims are estimated to be higher at failed banks that hold more assets or are part of a holding company. 

These results are available from the authors upon request. 

29 An interesting comparison can be made with Rolnick and Weber’s (1983) study of the U.S. Free Banking Era 

(1837–63). For banks that failed in the four states Rolnick and Weber study, they estimate that average losses to note 

holders per dollar ranged from 11 percent to 71 percent, with 15 percent to 26 percent being most typical. 
14

Although general creditor claims are typically a very small share of total claims, there are good 

reasons for believing that the holders of such claims may be in a position both to monitor and to influence 

the risk taking of their banks. General creditors frequently represent small businesses in a bank’s local 

community, businesses that support critical bank functions, and they constitute a class of claimants that 

will almost certainly lose in any resolution scenario. And even in a PA where the whole bank is sold, their 

contracts may not be renewed or honored by the acquiring bank. In addition, the bank’s business may be a 

large proportion of these firms’ total revenues. Such firms have a particularly strong incentive to monitor 

the riskiness of their client banks. Perhaps more importantly, some of these creditors, such as law firms 

and accountants, may be both especially knowledgeable about the riskiness of the bank and in an 

unusually strong position to influence that risk. In short, general creditors may be an important source of 

market discipline. 

The FDIC has always expected subordinated debt holders to lose 100 percent of their claims, and 

for this reason subordinated debt would be an ex ante source of market discipline. At our sample banks, 

however, subordinated debt was typically both a very unusual and an extremely small component of total 

claims. Furthermore, because of its long maturity, subordinated debt is not subject to runs by its holders. 

For all these reasons, we do not expect subordinated debt to be an instrument of market discipline at our 

sample banks. 

In contrast to uninsured deposits, general creditor claims, and subordinated debt, secured claims 

have always been expected by the FDIC to experience zero losses, a fact which suggests little scope for 

market discipline from secured claims. However, two other facts suggest that secured claims deserve 

some attention as we test for market discipline by examining changes in shares of bank liabilities: first, 

secured claims averaged 10 percent of total claims, and second, secured claims were present in 88 percent 

of the failed banks. 

IV. Tests for Quantity Discipline 

Here we investigate the behavior of claims in the five liability categories during the two years 

before a bank’s failure, concentrating on the three categories that are most likely to offer evidence of 
15

quantity market discipline. We compare this behavior with that of the same liability classes in riskstratified samples of banks that did not fail. After explaining our empirical strategy and then the 

procedures we used, we analyze the results and their implications. 

Empirical Strategy

Our tests for quantity discipline focus on quarterly changes in the shares of total claims of the five 

categories of claims identified in Section III. We test for whether the categories most likely to exhibit 

evidence of market discipline (in terms of changes in shares of total claims) are uninsured deposits, 

insured deposits (FDIC claims), and general creditor claims. This subsection begins with a brief rationale 

for our approach and then explains our empirical strategy in detail. 

Because the claim data analyzed in Section III are computed only for failed banks at the time of 

failure, historical analyses both of failed and non-failed banks require comparable historical claim data 

derived from other sources of information. Quarterly regulatory reports collected by the federal banking 

agencies provide such information.30 However, because the categories in these reports do not match 

exactly the claim categories used in the analysis of least-cost resolution methods, we must construct 

approximations to the least-cost-test categories.31 The resulting data are, for each bank, time series of 

claims that are defined the same across both failed and nonfailed banks.32

Several denominators could be chosen to scale the claim categories: the concurrent value of total 

claims, the starting value of a given claim (the value in quarter t-8), or the starting or ending value of total 

claims. We choose to scale the claim categories by the concurrent value of total claims. Importantly, the 

direction of change does not depend on the denominator used in the calculation, but the speed of the 

30 We refer to both bank Call Reports and Thrift Financial Reports as Call Reports. 

31 The definitions of the claim categories and the mapping to Call Report items are given in appendix A. 

32 All data are merger-adjusted. We merger adjust by collecting historical data for acquired banks and adding their 

balance sheets to those of the acquirers for each quarter as if the acquirer owned the acquired bank’s assets and 

liabilities throughout the entire period. This process allows easy comparison of balance sheet items over time and 

smooths large jumps in the data when a merger occurs. 
16

change does. For this reason, our analysis concentrates on the direction of change. In addition, under our 

approach the shares of the five claim categories are constrained to sum to 100 percent at each bank in 

each quarter. This approach is consistent with our objective of examining liability portfolio reallocations, 

but clearly does not allow us to determine if the dollar amounts of claims are changing. For example, in 

an extreme case, if dollars are flowing out of the bank in equal proportions across claim categories, we 

will detect no evidence of QD. However, the changes in proportions across claim categories are our 

primary concern. Therefore, use of the concurrent value of total claims as our reference point provides the 

most features that are consistent with our research objectives. 

Examination of changes both in the average size and in the average growth rates of assets and 

liabilities at our failed banks and at three groups of comparable banks that did not fail (defined below) 

indicates that by the end of 2008, funds were generally flowing out of failing and other very risky banks 

into safe banks. This pattern continued through 2010. Acharya and Mora (2011) find similar results. Thus, 

we conclude that perhaps the most straightforward indicator of QD-consistent portfolio reallocations—

funds flowing out of troubled banks into safe banks—was generally operative during the crisis.

Although examining changes in liability shares is common in the literature, our analysis makes an 

important innovation. It is well known that during this particular crisis policymakers’ responses, agents’ 

behavior, and virtually everyone’s expectations changed rapidly and were often unpredictable. As a result, 

assuming parameter stability over this period is highly problematic. We explicitly recognize such 

dynamics by examining changes in portfolio shares in each of the 12 quarters in 2008 through 2010. 

Thus, by design all relevant parameters are allowed to vary quarter by quarter.33 Because we wish to test 

for evidence of QD well before failure, we extend the analysis in each quarter back in time for 8 

quarters.34

33 This approach maintains extensive noise in the data and therefore creates a bias against finding evidence of QD. 

Additional analysis was done combining all quarters and results tend to be stronger. 

34 In contrast to estimating parameters quarter by quarter, looking for evidence of QD up to eight quarters before the 

current quarter is common in the literature. See Goldberg and Hudgins (2002) and Jordan (2000). 
17

To search for patterns of QD-consistent portfolio reallocations, we estimated the following 

equation for each of the five claim categories: 

ܥܵ௜௧ ൌ෍ߚ଴ǡ௝

ସ

௝ୀଵ

௧௜ߝ ൅ ௝ܩ௞ି௧ܦ௝ǡ௞ି௧ߚ෍෍൅

଻

௞ୀଵ

ସ

௝ୀଵ

(1)

Where

ܥܵ௜௧ = A given claim category’s percentage share of total claims at bank i in quarter t

ܦ௧ି௞ = Indicator variable for quarter t-k

ܩ = ௝Indicator for bank risk group 

ߚ = Estimated parameters 

ߝ௜௧ = Normally distributed random error 

By construction, the constant terms in (1), ȕ0,j, is the average share of that claim in the eighth quarter 

before the current quarter for risk group j. The other coefficients each measure the difference between the 

mean of the dependent variable in the eighth quarter before the current quarter and the mean in quarter t.

Thus, our coefficient estimates provide a clear picture of the pattern of average changes over the seven 

quarters before the current period for each claims category and by each bank risk group (see next 

paragraph). Standard errors are clustered at the bank risk group level. 

The bank risk groups represent the spectrum from safe banks to failed banks. We define our 

comparison groups of banks that did not fail by using a bank’s supervisory rating, or composite CAMELS 

rating, in a given quarter.35 A bank’s composite CAMELS rating is a confidential supervisory rating that 

is assigned to a bank by its primary federal regulator as part of the bank’s safety-and-soundness 

examination. The rating is an integer that ranges from 1 to 5. Banks rated 1 or 2 are considered to be 

either in excellent condition or fundamentally sound; banks rated 3 exhibit moderate to severe weaknesses 

but are deemed unlikely to fail; and banks rated 4 or 5 are considered to be either severely or critically 

unsound, with failure a distinct possibility. Although CAMELS ratings are not public, they are widely 

35 The letters in the acronym CAMELS stand for Capital adequacy, Asset quality, Management, Earnings, 

Liquidity, and Sensitivity to market risk. For more on the CAMELS rating system, see Federal Financial Institutions 

Examination Council (1996). 
18

viewed as a reasonably accurate broad-based measure of a bank’s financial condition.36 Our assumption is 

that if private liability holders are doing their own risk assessments, they will view as very risky the same 

banks that supervisors have rated 4 or 5 (group 1); will view as weak the same banks that supervisors 

have rated 3 (group 2); and will view as safe the same banks that supervisors have rated 1 or 2 (group 3). 

Put differently, we assume that private monitors may be approximately as good as (but not better than) 

supervisors in assessing a bank’s condition. Group 4 consists of banks that failed. 

The three risk groups for banks that did not fail are created separately for each quarter.37 Our 

choice of non-failed banks controls for bank size and location. We restrict the banks that did not fail to 

those that had total assets between $5 million and $35 billion, in order to be consistent with the asset-size 

of the failed banks. In addition, the banks that did not fail are restricted to those that were headquartered 

in a state in which at least one bank failed between 2008 and 2010.38 (We also excluded any bank with 

less than two years of data, essentially deleting de novo banks and their well-known idiosyncrasies.) This 

expanded sample allows us to observe differences in creditors’ behavior across the perceived riskiness of 

a creditor’s bank. 

In summary, we analyze the share of total claims for a particular claim category and track it eight 

quarters back through time at safe, weak, very risky, and failed banks. We do this every quarter starting 

from first quarter 2008 through the fourth quarter of 2010. We estimate a straightforward regression with 

indicators for the bank group and indicators for the number of quarters before the reference quarter. 

36 Using public data including “traditional proxies for CAMELS components,” Cole and White (2012, p. 27) argue 

that their results “offer strong support for the CAMELS approach to judging safety and soundness of commercial 

banks.” 

37 The samples of banks that did not fail omit banks that failed at any time during the sample period. Many banks in 

our samples of banks that did not fail appear in multiple quarters. Comparable tests using a random sample of banks 

that did not fail (without replacement) each quarter produced results that were qualitatively similar to those reported 

in the text. 

38 The reason we did not use a more precise matching methodology was that (again) our objective was to search for 

the general directions of portfolio reallocations during the crisis. 
19

Figure 1 is a graphical representation of our statistical approach for one bank group (failed banks) 

in one quarter (2009Q3) and across the claim classes.39 Visual inspection of the data suggests that the 

average share of insured claims was generally rising over the eight quarters before failure, the mean share 

of uninsured claims was generally falling, the average share of secured claims was stable until about three 

quarters before failure, and the mean share of general creditor claims was declining. Our regression 

equations shown in equation (1) subject such impressions to more rigorous tests. 

Results 

Our empirical approach clearly requires estimation of a large number of parameters. To limit the 

number of tables presented in this paper without excluding any substantive results, we now briefly 

discuss, but do not report, two general sets of results.40 One has to do with secured claims, the other with 

CAMELS 3 banks. (In the next part of this section, we analyze our main results.) 

First, we do not report the results for secured claims. Analysis of the FDIC’s expected loss rates 

concluded that secured claims should provide little market discipline. Regressions of the form described 

in equation (1) reinforce this conclusion. However, these regressions also indicate that the share of 

secured claims is quite variable over time. In addition, we previously reported that secured claims are, on 

average, a relatively large proportion of total claims. Both of these findings imply that movements in the 

shares of secured claims complicate the interpretation of results for the shares of insured deposits, 

uninsured deposits, and general creditor claims. This is especially the case for uninsured deposits and 

general creditor claims because each of those two categories has, on average, a much smaller share of 

total claims than insured depositors. On balance, the “noise” created by secured claims biases us toward 

not finding evidence of QD in movements in the shares of other claim categories.41

39 Subordinated debt is very small in magnitude and visually indistinguishable from zero. 

40 All results are available on request from the authors. 

41 This being said, the behavior of secured claims during the crisis may be an interesting topic for future research. 

Secured claims include liabilities of agents who should be well informed about the financial condition of their 

banks: other banks, Federal Home Loan Banks (FHLBs), and state and local governments. Indeed, the role of 
20

Second, we do not report the results for CAMELS 3 banks. Regression results for banks rated 

CAMELS 3 are similar to those for the CAMELS 4 and 5 banks and even the failed banks but are 

relatively ambiguous. This result, while not necessarily surprising, has an interesting and important 

behavioral interpretation. It suggests that creditors find it quite hard to assess the financial condition of 

CAMELS 3 banks and therefore, probably because of strong risk aversion, tend to treat them more like 

troubled than like safe banks. 

The full regression results for the claim categories of primary interest are reported in appendix B, 

tables B.1 through B.3.42 Because the number of estimated coefficients is so large, we have extracted 

portions of these tables and formatted them to highlight the main findings in tables 4 through 9. Tables 4-

6 report regression results for FDIC claims and tables 7-9 report results for uninsured claims at all but the 

CAMELS 3 group of banks. 

Tables 4 through 9 contain two panels each. The top panel of each pair reports results for 2008Q1 

through 2009Q4, and in that panel the independent variables consist of a constant term and an indicator 

variable for each of the seven quarters before the current quarter (t). To repeat: specifically for the failed 

banks, the current quarter (t) is the quarter in which the bank failed and the coefficients represent the 

change in the percentage share of the claim for each of the seven quarters prior to failure. For the nonfailed banks, the current quarter (t) is the quarter of the current Call Report. 

Major changes to deposit insurance coverage in 2008, implemented to help manage the crisis, 

were first reflected in Call Report data in 2009Q3. 43 To address this increase, we estimate two sets of 

FHLBs as “lender of next-to-last resort” during the crisis is already receiving significant attention (see Ashcraft, 

Bech, and Frame [2010] and Davidson and Simpson [2012]). 

42 As expected, the tests for subordinated debt find no evidence of quantity discipline and are not reported or 

discussed further. Again, all results are available on request. 

43 On October 3, 2008, President Bush temporarily raised the standard deposit insurance limit from $100,000 to 

$250,000, and on October 14, 100 percent deposit insurance was temporarily extended to non-interest-bearing 

transaction accounts. President Obama extended these “temporary” actions, and the Dodd-Frank Act permanently 

raised the standard maximum deposit insurance amount to $250,000. We note that all these actions should bias us 

toward not finding evidence of either quantity or price market discipline. Details on the reporting of these changes in 

Call Reports are in appendix A in the description of Uninsured Deposits. 
21

regressions for the four quarters in 2010. These results are shown in the bottom panels of tables 4 through 

9. First, as shown in the regressions for 2009Q4, the coefficients on the “One Quarter before Failure” (and 

one quarter before quarter t) indicator variable increase sharply in absolute value. We are unable to 

disentangle the effect of the change in reporting in 2009Q3 from potential changes due to QD. Therefore, 

we do not report coefficients on any post-2009Q3 variables in columns 9 through 12. Second, to 

explicitly address the break in series caused by the reporting change, for each quarter in 2010 we run new 

regressions where the constant term is 2009Q3. Each coefficient measures the difference between the 

mean of the dependent variable in 2009Q3 and the mean of the same variable in a given quarter before t 

(or before failure). Columns 13 through 16 in each table show these results. 

The change in the reporting of insured deposits does not affect our regressions for the shares of 

general creditor claims. Thus, tables 10 through 12 report only regressions similar to those in the top 

panels of tables 4 through 9. 

To facilitate understanding, in tables 4 through 12 the statistically significant declines in shares 

are shaded in dark grey, and the statistically significant increases in light grey. In addition, F-tests show 

that results for each of the bank groups are always statistically significantly different from each other at 

the 95 percent confidence level or better. Pairwise t-tests of individual coefficients, which compare 

coefficients from two groups at a time, show that for most quarters the failed-bank group and the riskybank group are statistically different from the CAMELS 1 and 2 bank group.44 Thus, all the differences 

between bank groups discussed below are supported by formal statistical tests. 

Analysis of Results 

The changes in the shares of FDIC claims are overwhelmingly positive at both the failed banks 

and the CAMELS 4 and 5 banks. At the failed banks, from the third quarter of 2008 through 2010, 

statistically significant increases began to occur at least two quarters before failure, and typically well 

44 All F- and t-tests are available on request from the authors. 
22

before that. At CAMELS 4 and 5 banks, the results are even stronger: throughout the entire period, FDIC 

shares typically began rising four or more quarters before quarter t.

CAMELS 1 and 2 banks show a strikingly different pattern of change in shares of FDIC claims. 

Here the direction of change is overwhelmingly negative, especially from 2008 through the first half of 

2010—the heart of the crisis. 

The dynamics of uninsured claim shares (tables 7–9) complement the dynamics for FDIC claims. 

The direction of changes in the shares of uninsured claims is overwhelmingly negative at both the failed 

banks and the CAMELS 4 and 5 banks. From mid-2008 through the first half of 2010, statistically 

significant decreases began to appear from two to seven quarters before either failure or quarter t.

As is true for the shares of FDIC claims, changes in the shares of uninsured claims at the 

CAMELS 1 and 2 banks are strikingly different. From the second quarter of 2008 through 2010, shares of 

uninsured claims are, with only a few exceptions, significantly increasing. 

The dynamics of GCC shares (tables 10–12), although suggestive of QD-consistent behavior, are 

less compelling than those for FDIC and uninsured depositor claims. Indeed, through 2008 the average 

general creditor does not appear to have been concerned about the financial condition of its bank—the 

statistical tests indicate claims rose or did not change. However, by the second half of 2009 this changes: 

significant declines typically occurred many quarters in advance of failure at the failed banks (or quarter t

at the CAMELS 4 and 5 banks). A similar pattern can be found in the CAMELS 1 and 2 banks although 

the growth patterns are larger in magnitude pre-2008 and decline patterns post-2008 are smaller in 

magnitude compared with the failed and risky bank groups. In all cases, the share of GCC is on average 

quite small—normally less than 2 percent. Thus, the movements in secured claims (documented above at 

the end of the discussion of empirical strategy) may well be obscuring QD-consistent behavior by general 

creditors.

The dynamic patterns of claim shares described above are highly consistent with quantity 

discipline: liability holders at very risky banks (failing and CAMELS 4 and 5 banks) convert their funds 

to insured claims, move their funds into safe banks (CAMELS 1 and 2 banks), or—in the case of GCC—
23

reduce their exposure to the bank with which they are doing business. Equally important, our results 

indicate that during the crisis, these QD-consistent portfolio reallocations tended to begin well before, 

often four or more quarters before, a bank failed. Such lead times seem long enough to signal to both 

banks and their supervisors that corrective actions can and should be taken. In addition, creditors 

generally seemed able to distinguish between very risky and safe banks. Indeed, the dynamics of liability 

shares at CAMELS 1 and 2 banks are consistent with creditors’ ability to identify them as safe. Finally, 

these patterns are observed despite the substantial increases in deposit insurance limits and other 

guarantees that were implemented at the height of the crisis. 

V. Tests for Price Discipline 

Creditors may also exert market discipline on relatively risky banks by demanding higher risk 

premiums, particularly on uninsured funds. Conversely, risky banks may seek either to retain or attract 

funds by being willing to pay higher interest rates, again particularly on uninsured funds. Acharya and 

Mora (2011) report that riskier banks had some success raising rates to attract deposits during the early 

part of the crisis. However, Ben-David, Palvia, and Spatt (2011) argue that as the crisis evolved, PD 

became inoperative; and Berger and Turk-Ariss (2012) find that PD probably declined during and after 

the crisis. Consistent with the literature established before the crisis, these newer results reach a similar 

conclusion—PD tends to dominate at relatively low levels of bank risk but that QD becomes more likely 

as tangible signs of serious weakness begin to appear. 

To test for PD, in principle we would compute a variety of spreads between interest rates on 

uninsured and insured liabilities at each bank. Then we would test whether, ceteris paribus, these spreads 

are positively related to bank risk and whether higher spreads succeeded in either attracting or retaining 

uninsured claims. In practice, our research strategy is driven by the fact that the only interest rates we can 
24

compute at our sample banks are very rough estimates of the average costs of uninsured and insured 

deposits as provided in Call Reports.45

Using these data, we conducted a number of tests for PD on the spread between the average 

interest rate on uninsured and insured deposits at individual banks in a given quarter.46 On balance, the 

results provide at best only weak evidence that PD was somewhat operative at our sample banks during 

the crisis. 

Spreads between the average interest rate on uninsured and insured deposits are, by and large, 

positive across all four bank groups (one of the groups is CAMELS 3 banks). Thus, perhaps the weakest 

condition for the existence of PD is supported. However, the spreads seem rather modest, virtually always 

less than about 50 basis points, and they even decline in the course of the crisis to around 30 basis 

points.47 More importantly, a stronger condition for the existence of PD, the condition that spreads should 

be larger at riskier banks, is rejected. Finally, tests for whether banks were either forced by creditors or 

chose on their own to use higher spreads to attract or retain uninsured deposits suggest that all four groups 

made such adjustments. However, it does not appear that the riskiest banks differed much from the safest 

banks in the amount of PD imposed.48

Whatever the interpretation, it is unclear how much credence to put into these PD results. On the 

one hand, the results are roughly consistent with previous findings that PD was weak or even nonexistent 

45 Almost all studies of PD that use deposit data suffer from this constraint. Partly for this reason, some authors have 

abandoned deposit data and examined the spread between yields on subordinated debt and comparable Treasury 

securities. That research strategy limits the analyst to relatively large banks that issue traded debt and is therefore not 

a strategy available to us. 

46 The results are available on request from the authors. 

47 Inspection of spreads between a sample of jumbo (partially uninsured) and nonjumbo deposit rates from a 

RateWatch database (https://www.rate-watch.com/) suggests our spread magnitudes are reasonable. RateWatch 

spreads were typically well under 100 basis points during the crisis. Indeed, many banks in the RateWatch sample 

did not post differences in rates between (partially) uninsured deposits and insured deposits. 

48 Back-of-the-envelope calculations suggest that, consistent with Maechler and McDill (2006), the CAMELS 1 and 

2 banks had a somewhat easier time using spreads to attract uninsured deposits than did very risky banks. 
25

during the crisis. On the other hand, our QD results indicate that creditors were generally able to 

distinguish between very risky and safe banks and thus had the knowledge to demand substantial risk 

premiums if warranted. Perhaps most important, using average cost data to test a hypothesis that is most 

likely to be observed in marginal prices is highly problematic. On balance, we conclude that our PD 

results should be viewed as at most only suggestive of weak price discipline during the crisis. 

VI. Conclusion and Policy Implications 

Based on a unique dataset of the FDIC’s expectations about losses to uninsured creditors in banks 

that failed during the 2008-2010 crisis, we hypothesize that the categories of liabilities most likely to 

exhibit evidence of market discipline are uninsured deposits, insured deposits, and general creditor 

claims. Empirical tests using all liability categories at both failed and non-failed banks are consistent with 

quantity market discipline, in which liability holders monitor their banks and reallocate their portfolios in 

ways that protect them from losses. These portfolio reallocations tend to begin far enough in advance to 

signal both to banks and to their supervisors that corrective actions can and should be taken. Although 

interest rates on uninsured deposits could provide similar signals and discipline, our results suggest that 

the data needed to reliably do price analysis are not readily available. However, consistent with the 

literature, our results also suggest that during the crisis, quantity discipline was relatively strong and price 

market discipline was relatively weak. 

Our findings support several important policy implications. First, they strongly reinforce and 

enrich the view long held by bank supervisors and market participants that bank liability flows are 

powerful indicators of a bank’s health.49 Our results emphasize that the shares of liabilities held in 

uninsured and insured deposits and general creditor claims should be monitored as part of supervisory 

early-warning systems for community and medium-sized banks. Second, although most of the failures 

from 2008 to 2010 period were of community and medium-sized banks, it seems reasonable to conclude 

that such advice applies to the monitoring of larger banks as well. 

49 Acharya and Mora (2011) reach a similar conclusion. 
26

An important corollary of these implications relates to regulatory collection and disclosure of 

data. Our results indicate that supervisory data collections should explicitly include quantity flows by 

creditor categories, particularly insured and uninsured deposits, and that accurate disclosure of such data 

would encourage market discipline.50 Indeed, the difficulties we experienced constructing such at-risk 

claims from currently available data argue strongly that appropriate changes in regulatory data collection 

and disclosure should be important policy priorities. These conclusions hold with even more force for 

current regulatory collections of data on interest rates paid on similar categories of bank liabilities, i.e. 

insured and uninsured deposits. 

Finally, our findings support the view that market discipline can be an effective complement to 

safety-and-soundness supervision by bank regulators. We are not suggesting that market discipline before 

and during the crisis was enough by itself to control bank risk. Clearly, many banks failed and many 

others became severely troubled. However, many troubled banks recovered, and our results are consistent 

with the conclusion that market discipline is potentially important when creditors are at risk of loss. More 

generally, our results support the view that policymakers’ active encouragement of market discipline will 

be beneficial 

50 Schaeck (2008) reaches the same conclusion in his study of FDIC losses and their relationship to bank liability 

structure.
27

.

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32

(1) (2) (3) (4) (5) (6)

Northeast South Midwest Southwest West All

2008Q1 0 0 2 0 0 2

(0.6)

2008Q2 0 1 1 0 0 2

(0.6)

2008Q3 0 3 1 0 4 8

(2.5)

2008Q4 0 5 2 2 3 12

(3.8)

2009Q1 1 6 5 0 9 21

(6.6)

2009Q2 1 8 7 0 8 24

(7.5)

2009Q3 4 16 17 6 7 50

(15.7)

2009Q4 0 16 15 5 9 45

(14.2)

2010Q1 3 15 9 3 11 41

(12.9)

2010Q2 1 12 18 2 9 42

(13.2)

2010Q3 4 19 8 1 9 41

(12.9)

2010Q4 3 13 8 2 4 30

(9.4)

All 17 114 93 21 73 318

(5.3) (35.8) (29.2) (6.6) (23.0) (100.0)

Notes: 

1. The Northeast region includes Maine, New Hampshire, Vermont, Massachusetts, Connecticut, Rhode Island, New York, 

Region

Quarter

Table 1

Number of Bank Failures by Quarter and Region

Nevada, Alaska, and Hawaii. 

2. The parenthetical numbers in column 6 and in the final row are percentages. 

Pennsylvania, New Jersey, Deleware, Maryland, and DC. The South includes West Virginia, Virginia, North Carolina, South Carolina, 

Georgia, Florida, Alabama, Mississippi, Louisiana, Arkansas, Tennessee, and Kentucky. Midwest includes Ohio, Michigan, Indiana,

Illinois, Wisconsin, Minnesota, Iowa, Missouri, Kansas, Nebraska, North Dakota, and South Dakota. The Southwest includes Oklahama, 

Texas, New Mexico, and Arizona. The West includes California, Oregon, Washington, Idaho, Montana, Wyoming, Colarado, Utah,
33

(1) (2) (3) (4)

TA < $1B $1B <= TA <= $10B TA > $10B All

PAL 179 33 6 218

(68.6)

PA 67 4 0 71

(22.3)

PI 7 3 1 11

(3.5)

PO 14 4 0 18

(5.7)

All 267 44 7 318

(84.0) (13.8) (2.2) (100.0)

1. PAL is a purchase and assumption transaction with FDIC loss sharing. PA is a purchase and assumption transactiondeposits on the liabilities side of the failed bank's balance sheet. PO is a deposit payout transaction.2. The parenthetical numbers in column 4 and in the final row are percentages.

Total Assets (TA) Size Class

Resolution 

Type

Table 2

Number of Bank Failures by Resolution Type and Size, 2008 to 2010

Notes: without FDIC loss sharing. PI is a purchase and assumption transaction where the acquirer assumes only insured
34

(1) (2) (3) (4) (5)

Resolution Uninsured Sub Secured

Type FDIC Deposits GCC Debt Claims

PAL 25.8 0.0 96.8 100.0 0.0

(10.7) (-) (20.1) (-) (-)

PA 33.3 *** 0.0 98.6 100.0 0.0

(13.8) (-) (11.9) (-) (-)

PI 28.8 28.4 100.0 100.0 0.0

(12.2) (12.8) (-) (-) (-)

PO 37.8 *** 38.4 + 94.4 100.0 0.0

(12.9) (14.0) (23.6) (-) (-)

All 28.3 34.4 97.2 100.0 0.0

(12.2) (14 .2) (18 .4) (-) (-)

PAL 218 0 216 18 197

PA 71 0 71 2 60

PI 11 10 11 2 11

PO 18 15 18 1 12All 318 25 316 23 280

Mean 89.9 2.3 0.7 1.2 10.4Std Deviation (8 .6) (4 .3) (1 .0) (0 .8) (8 .1)

Notes: 1. Mean percent of total claims in a category. Standard deviations in parentheses.*** Significantly different from PAL at the one percent confidence level; ** at the five percent level.+ Significantly different from PI at the ten percent confidence level.

Table 3

Expected Loss Rates by Resolution Type and Claims Category, 2008 to 2010

Claims Category

Panel A: Mean and Standard Deviation of Expected Loss Rates1

Panel B: Number of Observations

Panel C: Percent of Total Claims
35

(1) (2) (3) (4) (5) (6) (7) (8)

2008Q1 2008Q2 2008Q3 2008Q4 2009Q1 2009Q2 2009Q3 2009Q4

Constant (Eight Quarters before Failure) 83.0*** 48.0** 51.6*** 54.0*** 56.5*** 57.6*** 66.2*** 65.0***Seven Quarters before Failure -0.7 -2.8*** -0.4 3.8 -0.7 3.2 -0.0 -2.5***Six Quarters before Failure -2.3* -1.6 0.0 4.2 -1.8 2.7 2.3** -3.2*Five Quarters before Failure -3.0 37.1 1.0 7.5* 3.2 3.1 1.9* -0.4Four Quarters before Failure -3.6 36.3 4.9** 7.2* 4.8 4.1 6.8*** 2.9**Three Quarters before Failure -3.6*** 34.5 10.6** 5.0 5.2 6.2 7.9*** 4.3***Two Quarters before Failure -5.0*** 36.1 17.3*** 17.6*** 9.4* 7.9* 9.4*** 6.0***One Quarter before Failure -2.8 39.3 25.5*** 15.3*** 12.8** 8.8** 9.6*** 17.9***Number of Banks 2 2 8 12 21 24 50 45R-Squared 0.951 0.950 0.951 0.952 0.952 0.953 0.956 0.954

(9) (10) (11) (12) (13) (14) (15) (16)

2010Q1 2010Q2 2010Q3 2010Q4 2010Q1 2010Q2 2010Q3 2010Q4

Constant (Eight Quarters before Failure) 66.5*** 63.8*** 66.8*** 66.6*** 84.8*** 84.1*** 82.7*** 82.0***Seven Quarters before Failure 1.0 3.5** 1.2** 0.8Six Quarters before Failure 3.4*** 3.5* 2.4*** 3.1*Five Quarters before Failure 4.3*** 6.2*** 3.3***Four Quarters before Failure 5.0*** 6.1*** 1.3Three Quarters before Failure 6.9*** 1.5** 2.8***Two Quarters before Failure -0.0 2.4*** 2.3**One Quarter before Failure 1.1* 2.5*** 3.6*** 4.3***Number of Banks 41 42 41 30 41 42 41 30R-Squared 0.954 0.955 0.956 0.956 0.971 0.971 0.972 0.972

Table 4

FDIC Claims

Failed Banks at Quarter t

***=Significantly different from zero at the 99 percent confidence level; **=at the 95 percent confidence level; * at the 90 percent confidence level. Darkly shaded cells indicate negative and significant coeffients and lightly shaded cells indicate positive and significant coeffients.
36

(1) (2) (3) (4) (5) (6) (7) (8)

2008Q1 2008Q2 2008Q3 2008Q4 2009Q1 2009Q2 2009Q3 2009Q4

Constant (Eight Quarters before Quarter t) 69.7*** 68.9*** 67.7*** 67.0*** 67.0*** 67.1*** 66.0*** 65.2***Seven Quarters before Quarter t 0.1 -0.1 0.0 1.9*** 0.4 -0.3 -0.7*** 0.4*Six Quarters before Quarter t 0.7 0.1 2.0*** 2.3*** 0.3 -0.8*** -0.1 0.6*Five Quarters before Quarter t 1.1 1.8* 2.1*** 1.8*** -0.1 -0.2 0.3 2.1***Four Quarters before Quarter t 3.4** 2.6** 1.7** 1.7** 0.1 0.5 1.9*** 2.7***Three Quarters before Quarter t 4.4*** 2.1* 1.9** 2.4*** 0.8 2.0*** 2.5*** 3.8***Two Quarters before Qarter t 4.0*** 2.5** 2.4*** 3.3*** 2.6*** 2.8*** 3.5*** 4.4***One Quarter before Quarter t 4.4*** 3.0** 3.7*** 5.1*** 3.2*** 3.6*** 4.1*** 15.7***Number of Banks 76 98 142 185 264 370 493 586R-Squared 0.951 0.951 0.950 0.951 0.952 0.952 0.953 0.956

(9) (10) (11) (12) (13) (14) (15) (16)

2010Q1 2010Q2 2010Q3 2010Q4 2010Q1 2010Q2 2010Q3 2010Q4

Constant (Eight Quarters before Quarter t) 66.0*** 66.0*** 66.8*** 67.2*** 80.7*** 80.5*** 80.2*** 80.2***Seven Quarters before Quarter t 0.1 1.2*** 0.3 1.0***Six Quarters before Quarter t 1.4*** 1.6*** 1.4*** 1.4***Five Quarters before Quarter t 1.9*** 2.7*** 1.7***Four Quarters before Quarter t 3.0*** 3.1*** 0.7***Three Quarters before Quarter t 3.4*** 0.6*** 1.7***Two Quarters before Quarter t 0.6*** 1.6*** 2.3***One Quarter before Quarter t 0.8*** 1.6*** 2.3*** 3.1***Number of Banks 666 740 761 762 666 740 761 762R-Squared 0.954 0.955 0.956 0.956 0.971 0.971 0.972 0.972

Table 5

FDIC Claims

CAMELS 4 and 5 at Quarter t

***=Significantly different from zero at the 99 percent confidence level; **=at the 95 percent confidence level; * at the 90 percent confidence level. Darkly shaded cells indicate negative and significant coeffients and lightly shaded cells indicate positive and significant coeffients.
37

(1) (2) (3) (4) (5) (6) (7) (8)

2008Q1 2008Q2 2008Q3 2008Q4 2009Q1 2009Q2 2009Q3 2009Q4

Constant (Eight Quarters before Quarter t) 71.2*** 71.4*** 71.3*** 71.3*** 72.2*** 72.2*** 71.9*** 71.3***Seven Quarters before Quarter t 0.1** -0.2*** -0.0 0.6*** -0.1** -0.5*** -0.7*** 0.1Six Quarters before Quarter t -0.1* -0.3*** 0.5*** 0.5*** -0.7*** -1.2*** -0.6*** -0.5***Five Quarters before Quarter t -0.2** 0.3*** 0.4*** -0.0 -1.4*** -1.2*** -1.2*** -0.5***Four Quarters before Quarter t 0.4*** 0.2** -0.1 -0.8*** -1.3*** -1.7*** -1.2*** -0.9***Three Quarters before Quarter t 0.3*** -0.4*** -0.8*** -0.7*** -1.8*** -1.7*** -1.6*** -0.4***Two Quarters before Quarter t -0.2** -1.1*** -0.8*** -1.2*** -1.8*** -2.1*** -1.1*** -0.4***One Quarter before Quarter t -0.9*** -1.0*** -1.3*** -1.2*** -2.2*** -1.6*** -1.2*** 8.9***Number of Banks 6,537 6,402 6,235 6,059 5,859 5,653 5,401 5,200R-Squared 0.951 0.951 0.950 0.951 0.952 0.952 0.953 0.956

(9) (10) (11) (12) (13) (14) (15) (16)

2010Q1 2010Q2 2010Q3 2010Q4 2010Q1 2010Q2 2010Q3 2010Q4

Constant (Eight Quarters before Quarter t) 71.5*** 71.0*** 70.8*** 70.4*** 80.3*** 80.3*** 80.3*** 80.3***Seven Quarters before Quarter t -0.5*** -0.1* -0.4*** 0.5***Six Quarters before Quarter t -0.6*** -0.5*** 0.2** 0.5***Five Quarters before Quarter t -1.0*** 0.0 0.1Four Quarters before Quarter t -0.5*** 0.0 -0.2***Three Quarters before Quarter t -0.5*** -0.2*** 0.2***Two Quarters before Quarter t -0.2*** 0.2*** 0.2***One Quarter before Quarter t -0.2*** 0.2** 0.2*** 0.1Number of Banks 5,048 4,944 4,909 4,864 5,048 4,944 4,909 4,864R-squared 0.954 0.955 0.956 0.956 0.971 0.971 0.972 0.972

Table 6

FDIC Claims

CAMELS 1 and 2 at Quarter t

***=Significantly different from zero at the 99 percent confidence level; **=at the 95 percent confidence level; * at the 90 percent confidence level. Darkly shaded cells indicate negative and significant coeffients and lightly shaded cells indicate positive and significant coeffients.
38

(1) (2) (3) (4) (5) (6) (7) (8)

2008Q1 2008Q2 2008Q3 2008Q4 2009Q1 2009Q2 2009Q3 2009Q4

Constant (Eight Quarters before Failure) 2.3*** 32.3* 24.9*** 31.9*** 30.1*** 27.7*** 21.5*** 20.8***Seven Quarters before Failure -0.5 -1.0* 1.2 -2.3 0.0 -3.9 -1.1 -0.6Six Quarters before Failure -0.9 1.8 3.2** -2.4 0.2 -4.8 -2.7*** -0.1Five Quarters before Failure -0.4 -27.1 1.7 -7.1 -4.8 -4.9 -2.1* -2.5**Four Quarters before Failure 0.8 -26.5 -0.8 -6.3 -6.5 -4.5 -6.6*** -4.1***Three Quarters before Failure -0.6 -23.7 -0.9 -0.8 -7.4 -5.1 -5.9*** -2.1Two Quarters before Failure -0.7 -26.3 -6.8* -13.1*** -11.5** -6.7 -4.0** -2.5One Quarter before Failure -0.2 -22.8 -11.8*** -11.2*** -13.6*** -4.1 -3.5* -13.6***Number of Banks 2 2 8 12 21 24 50 45R-Squared 0.586 0.611 0.635 0.604 0.613 0.641 0.665 0.627

(9) (10) (11) (12) (13) (14) (15) (16)

2010Q1 2010Q2 2010Q3 2010Q4 2010Q1 2010Q2 2010Q3 2010Q4

Constant (Eight Quarters before Failure) 20.4*** 22.8*** 20.8*** 20.6*** 6.8*** 6.3*** 8.0*** 8.1***Seven Quarters before Failure -0.8 -2.9** -0.2 0.6Six Quarters before Failure -2.5** -2.8 -0.2 -0.9Five Quarters before Failure -2.9** -4.2** -1.2Four Quarters before Failure -2.0 -3.0* -1.3Three Quarters before Failure -3.4** -0.9 -1.3Two Quarters before Failure 0.8 -0.5 -0.7One Quarter before Failure -1.1** -0.6 -1.6* -2.3*Number of Banks 41 42 41 30 41 42 41 30R-Squared 0.644 0.645 0.650 0.655 0.410 0.487 0.519 0.416

Table 7

Uninsured Claims

Failed Banks at Quarter t

***=Significantly different from zero at the 99 percent confidence level; **=at the 95 percent confidence level; * at the 90 percent confidence level. Darkly shaded cells indicate negative and significant coeffients and lightly shaded cells indicate positive and significant coeffients.
39

(1) (2) (3) (4) (5) (6) (7) (8)

2008Q1 2008Q2 2008Q3 2008Q4 2009Q1 2009Q2 2009Q3 2009Q4

Constant (Eight Quarters before Quarter t) 17.8*** 18.8*** 19.9*** 20.3*** 20.6*** 20.7*** 21.2*** 21.3***Seven Quarters before Quarter t -0.2 0.3 0.2 -1.5*** -0.7** -0.4* 0.2 -0.8***Six Quarters before Quarter t -0.8 0.5 -1.3* -2.1*** -1.2*** -0.5 -0.8** -1.9***Five Quarters before Quarter t -0.8 -0.7 -1.6** -2.0*** -1.4*** -1.2*** -2.1*** -3.0***Four Quarters before Quarter t -2.5* -1.2 -1.3* -2.2*** -1.7*** -2.6*** -3.2*** -3.0***Three Quarters before Quarter t -3.4** -0.9 -1.5* -3.3*** -2.9*** -3.7*** -3.1*** -2.9***Two Quarters before Quarter t -3.2** -1.3 1.2 -4.2*** -4.3*** -3.5*** -0.4 -2.7***One Quarter before Quarter t -3.7** 1.8 -0.1 -5.6*** -4.0*** -0.7 -0.4 -13.2***Number of Banks 76 98 142 185 264 370 493 586R-Squared 0.586 0.611 0.635 0.604 0.613 0.641 0.665 0.627

(9) (10) (11) (12) (13) (14) (15) (16)

2010Q1 2010Q2 2010Q3 2010Q4 2010Q1 2010Q2 2010Q3 2010Q4

Constant (Eight Quarters before Quarter t) 20.2*** 19.6*** 19.0*** 19.2*** 8.2*** 8.5*** 8.7*** 8.8***Seven Quarters before Quarter t -1.0*** -0.9*** 0.1 0.3*Six Quarters before Quarter t -2.0*** -0.9*** 0.5* 0.4*Five Quarters before Quarter t -2.0*** -0.6** 0.6**Four Quarters before Quarter t -1.7*** -0.4 -0.2Three Quarters before Quarter t -1.5*** -0.2 -0.6***Two Quarters before Quarter t -0.1 1.5*** -0.8***One Quarter before Quarter t -0.2 1.5*** 1.3*** -1.3***Number of Banks 666 740 761 762 666 740 761 762R-Squared 0.644 0.645 0.650 0.655 0.410 0.487 0.519 0.416

Table 8

Uninsured Claims

CAMELS 4 and 5 at Quarter t

***=Significantly different from zero at the 99 percent confidence level; **=at the 95 percent confidence level; * at the 90 percent confidence level. Darkly shaded cells indicate negative and significant coeffients and lightly shaded cells indicate positive and significant coeffients.
40

(1) (2) (3) (4) (5) (6) (7) (8)

2008Q1 2008Q2 2008Q3 2008Q4 2009Q1 2009Q2 2009Q3 2009Q4

Constant (Eight Quarters before Quarter t) 16.0*** 15.4*** 15.4*** 15.9*** 15.5*** 15.0*** 15.1*** 15.4***Seven Quarters before Quarter t -0.6*** 0.1** 0.6*** -0.2*** -0.2*** 0.1* 0.5*** -0.1*Six Quarters before Quarter t -0.5*** 0.7*** 0.3*** -0.5*** -0.1** 0.5*** 0.4*** -0.2**Five Quarters before Quarter t 0.1 0.5*** 0.1 -0.4*** 0.3*** 0.4*** 0.3*** -0.5***Four Quarters before Quarter t -0.2** 0.2*** 0.2** 0.0 0.2** 0.3*** -0.0 0.1Three Quarters before Quarter t -0.4*** 0.3*** 0.6*** -0.1 0.1 -0.0 0.6*** 0.6***Two Quarters before Quarter t -0.4*** 0.7*** 5.6*** -0.2** -0.3*** 0.6*** 6.1*** 0.7***One Quarter before Quarter t 0.1 5.7*** 5.4*** -0.6*** 0.3*** 6.1*** 6.2*** -7.8***Number of Banks 6,537 6,402 6,235 6,059 5,859 5,653 5,401 5,200R-Squared 0.586 0.611 0.635 0.604 0.613 0.641 0.665 0.627

(9) (10) (11) (12) (13) (14) (15) (16)

2010Q1 2010Q2 2010Q3 2010Q4 2010Q1 2010Q2 2010Q3 2010Q4

Constant (Eight Quarters before Quarter t) 15.3*** 15.3*** 15.1*** 15.8*** 7.6*** 7.6*** 7.7*** 7.7***Seven Quarters before Quarter t -0.1* -0.2*** 0.6*** 0.4***Six Quarters before Quarter t -0.4*** 0.4*** 1.0*** 0.5***Five Quarters before Quarter t 0.3*** 0.8*** 1.1***Four Quarters before Quarter t 0.7*** 0.9*** 0.4***Three Quarters before Quarter t 0.8*** 0.4*** 0.4***Two Quarters before Quarter t 0.4*** 5.0*** 0.5***One Quarter before Quarter t 0.4*** 5.0*** 5.0*** 0.7***Number of Banks 5,048 4,944 4,909 4,864 5,048 4,944 4,909 4,864R-Squared 0.644 0.645 0.650 0.655 0.410 0.487 0.519 0.416

Table 9

Uninsured Claims

CAMELS 1 and 2 at Quarter t

***=Significantly different from zero at the 99 percent confidence level; **=at the 95 percent confidence level; * at the 90 percent confidence level. Darkly shaded cells indicate negative and significant coeffients and lightly shaded cells indicate positive and significant coeffients.
41

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

2008Q1 2008Q2 2008Q3 2008Q4 2009Q1 2009Q2 2009Q3 2009Q4 2010Q1 2010Q2 2010Q3 2010Q4

Constant (Eight Quarters before Failure) 0.7* 0.8*** 1.2** 0.6*** 0.6*** 3.8 1.3*** 2.7** 1.8** 1.0*** 0.9*** 0.8***Seven Quarters before Failure 0.0 0.3* 10.1 0.9 0.2 0.5 0.8** 1.2 -0.2 -0.2 -0.3** -0.3*Six Quarters before Failure -0.0 0.0 8.4 0.8** 0.4** 0.4** -0.2 0.4 -0.6 -0.4* -0.4*** -0.2*Five Quarters before Failure 1.0** -0.2*** 9.0 0.4 0.2 0.3 0.1 -0.6 -0.8* -0.2 -0.3* -0.4**Four Quarters before Failure 0.9 1.4 7.5 0.4** 0.2 -0.5 -0.3 -0.9* -1.1 -0.5** -0.3** -0.3Three Quarters before Failure 2.4*** -0.5*** 2.5 0.5 -0.1 -1.0 -0.6*** -1.3** -1.1 -0.5** -0.4** -0.4Two Quarters before Failure 3.9*** -0.2 2.3 0.8 -0.2 -0.2 -0.7*** -1.6* -1.2* -0.5** -0.4*** -0.3One Quarter before Failure 0.5 -0.4** 0.3 -0.2 0.1 -2.0 -0.7*** -1.9* -1.0 -0.4 -0.4** -0.3Number of Banks 2 2 8 12 21 24 50 45 41 42 41 30R-Squared 0.049 0.051 0.055 0.056 0.058 0.058 0.058 0.058 0.057 0.057 0.055 0.053

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

2008Q1 2008Q2 2008Q3 2008Q4 2009Q1 2009Q2 2009Q3 2009Q4 2010Q1 2010Q2 2010Q3 2010Q4

Constant (Eight Quarters before Quarter t) 0.6*** 0.5*** 0.6*** 1.7*** 1.8*** 1.7*** 1.6*** 1.7*** 1.4*** 1.7*** 1.4*** 1.1***Seven Quarters before Quarter t 0.0 0.0* 0.4*** -0.2 0.1 -0.0 0.1** -0.1 0.2*** -0.3** -0.3** -0.2**Six Quarters before Quarter t -0.0 0.3*** 0.2*** -0.1 0.0 0.2 -0.1 0.1 -0.1 -0.6*** -0.4*** -0.0Five Quarters before Quarter t 0.6** 0.3*** 0.5*** -0.1 0.1 -0.0 0.2** -0.3 -0.4** -0.8*** -0.3*** -0.0Four Quarters before Quarter t 0.4*** 0.3*** 0.4*** -0.1 0.0 0.2 -0.1 -0.6*** -0.5*** -0.6*** -0.3** -0.1*Three Quarters before Quarter t 0.5*** 0.3*** 0.5*** 0.1 0.2 -0.1 -0.5** -0.6*** -0.4*** -0.6*** -0.4*** -0.2***Two Quarters before Quarter t 0.5*** 0.3*** 0.6** -0.1 -0.2 -0.7** -0.5** -0.5*** -0.4*** -0.7*** -0.5*** -0.3***One Quarter before Quarter t 0.9** 0.4** 0.4*** -0.6 -0.8* -0.6** -0.3** -0.5*** -0.5*** -0.8*** -0.5*** -0.3***Number of Banks 76 98 142 185 264 370 493 586 666 740 761 762R-Squared 0.049 0.051 0.055 0.056 0.058 0.058 0.058 0.058 0.057 0.057 0.055 0.053

Table 11

General Creditor Claims

CAMELS 4 and 5 at Quarter t

***=Significantly different from zero at the 99 percent confidence level; **=at the 95 percent confidence level; * at the 90 percent confidence level. Darkly shaded cells indicate negative and significant coeffients and lightly shaded cells indicate positive and significant coeffients.

Table 10

General Creditor Claims

Failed Banks at Quarter t

***=Significantly different from zero at the 99 percent confidence level; **=at the 95 percent confidence level; * at the 90 percent confidence level. Darkly shaded cells indicate negative and significant coeffients and lightly shaded cells indicate positive and significant coeffients.
42

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

2008Q1 2008Q2 2008Q3 2008Q4 2009Q1 2009Q2 2009Q3 2009Q4 2010Q1 2010Q2 2010Q3 2010Q4

Constant (Eight Quarters before Quarter t) 1.0*** 0.9*** 1.0*** 1.7*** 1.6*** 1.7*** 1.8*** 1.8*** 1.7*** 1.8*** 1.8*** 1.8***Seven Quarters before Quarter t 0.0 0.1*** 0.7*** -0.1*** 0.1*** 0.1*** -0.0 -0.1*** 0.2*** 0.0 -0.1** -0.2***Six Quarters before Quarter t 0.1*** 0.8*** 0.6*** 0.0 0.2*** 0.1*** -0.2*** 0.1* 0.2*** -0.0 -0.2*** -0.1***Five Quarters before Quarter t 0.8*** 0.7*** 0.7*** 0.1*** 0.2*** -0.0 0.0 0.1* 0.1** -0.2*** -0.2*** -0.1**Four Quarters before Quarter t 0.7*** 0.8*** 0.8*** 0.1*** 0.1* 0.2*** 0.1 0.0 -0.1 -0.2*** -0.2*** -0.2***Three Quarters before Quarter t 0.8*** 0.9*** 0.8*** -0.0 0.3*** 0.2*** -0.0 -0.1*** -0.0 -0.2*** -0.3*** -0.3***Two Quarters before Quarter t 0.9*** 0.9*** 0.7*** 0.2*** 0.3*** 0.1* -0.2*** -0.1** -0.0 -0.3*** -0.4*** -0.3***One Quarter before Quarter t 0.9*** 0.8*** 0.9*** 0.2*** 0.2*** -0.1* -0.2*** -0.1* -0.1** -0.4*** -0.3*** -0.2***Number of Banks 6,537 6,402 6,235 6,059 5,859 5,653 5,401 5,200 5,048 4,944 4,909 4,864R-Squared 0.049 0.051 0.055 0.056 0.058 0.058 0.058 0.058 0.057 0.057 0.055 0.053

Table 12

General Creditor Claims

CAMELS 1 and 2 at Quarter t

***=Significantly different from zero at the 99 percent confidence level; **=at the 95 percent confidence level; * at the 90 percent confidence level. Darkly shaded cells indicate negative and significant coeffients and lightly shaded cells indicate positive and significant coeffients.
43

0%

90%80%70%60%50%40%30%20%10%

100%

2007Q3 2007Q4 2008Q1 2008Q2 2008Q3 2008Q4 2009Q1 2009Q2

Figure 1: Example of Changes in Composition of Liabilities Ending 2009Q3

Failed Banks, Amount of Claims as a Percentage of Total Claims (Average)

FDIC Claims

Uninsured Claims

Secured Claims

General Creditor Claims
44

FDIC Claim

Uninsured Claims

General Creditor Claims

Subordinated Claims

Secured Claims

Call Report Line Items Used

Schedule RC, Line 13 (RC 13)

RC-G 1.a

RC 13.b

Linear interpolation between year-end reported values. RC-E 1.e

For 2005Q4-2006Q3 RC 20

For 2006Q4 and after: Includes Other Unsecured Borrowing and 

Unsecured Federal Funds

For 2006Q3 and before: Fed Funds and Repos Purchased RC 14

For 2006Q4 and after: The amount of fed funds purchased that are 

secured by pledged securities plus securities sold under agreements 

to repurchase on a consolidated basis

RC-M 10.a, RC-14.b

For 2006Q4 and after: Fed funds and repos purchasef less the 

amount of fed funds purchased that are secured.

RC 14.a, RC-M 10.a

For 2006Q3 and before: not defined

For 2006Q4 or after: Other borrowed money less the amount of other 

borrowings that are secured by pledged securities less other 

liabilities from the FHLB

RC-M 5.c, 10.b, 5.a

For 2006Q3 and before: not defined

RC 15

RC 19

FHLB Advances RC-M 5.a

For 2005Q4-2006Q3 RC 22

For 2006Q4 and after: RC 27.b

For 2005Q4 and before: Bank's liability on acceptances plus other 

borrowings

RC 18, RC-M 5.b

For 2006Q1-2006Q3: Other borrowings RC-M 5.b

For 2006Q4 and after: The amount of other borrowing that are 

secured

RC-M 10.b

For 2006Q2-2009Q2: Amount of large deposit accounts less 

$100,000 times the number of large deposit accounts plus the amount 

of large deposit retirement accounts less $250,000 times the number 

of large deposit reitrement accounts

For 2009Q3 and after: Amount of large deposit accounts less 

$250,000 times the number of large deposit accounts plus the amount 

of large deposit retirement accounts less $250,000 times the number 

of large deposit reitrement accounts

Uninsured Deposits For 2005Q4-2006Q1: Amount of large deposit accounts less 

$100,000 times the number of large deposit accounts

RC-O 1.b(1), 1.b(2), 1.d(1), 

1.d(2)

Total Deposits + Interest Accrued on Deposits and Unpaid í Uninsured Deposits - Foreign Deposits

Uninsured Deposits í Preferred Deposits

Other Liabilities + Trading Liabilities + Foreign Deposits í Interest Accrued on Deposits and Unpaid

Preferred Deposits

Other Liabilities

Trading Liabilities

Secured Fed Funds and Repos Purchased

Other Unsecured Borrowing

Foreign Deposits

Subordinated Notes and Debentures 

Appendix A

Definition of Receivership Claims

Other Secured Borrowing

Interest Accrued on Deposits and Unpaid

FHLB Advances + Preferred Deposits + Secured Fed Funds and Repos Purchased + Minority Interest in Consolidated 

Subs + Other Secured Borrowing

Subordinated Notes and Debentures

Total Deposits

Minority Interest in Consolidated Subs

Unsecured Federal Funds
45

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15) (16)

2008Q1 2008Q2 2008Q3 2008Q4 2009Q1 2009Q2 2009Q3 2009Q4 2010Q1 2010Q2 2010Q3 2010Q4 2010Q1 2010Q2 2010Q3 2010Q4

CAMELS 1,2 Constant (Eight Quarters before Quarter t) 71.2*** 71.4*** 71.3*** 71.3*** 72.2*** 72.2*** 71.9*** 71.3*** 71.5*** 71.0*** 70.8*** 70.4*** 80.3*** 80.3*** 80.3*** 80.3***

Seven Quarters before Quarter t 0.1** -0.2*** -0.0 0.6*** -0.1** -0.5*** -0.7*** 0.1 -0.5*** -0.1* -0.4*** 0.5***Six Quarters before Quarter t -0.1* -0.3*** 0.5*** 0.5*** -0.7*** -1.2*** -0.6*** -0.5*** -0.6*** -0.5*** 0.2** 0.5***Five Quarters before Quarter t -0.2** 0.3*** 0.4*** -0.0 -1.4*** -1.2*** -1.2*** -0.5*** -1.0*** 0.0 0.1Four Quarters before Quarter t 0.4*** 0.2** -0.1 -0.8*** -1.3*** -1.7*** -1.2*** -0.9*** -0.5*** 0.0 -0.2***Three Quarters before Quarter t 0.3*** -0.4*** -0.8*** -0.7*** -1.8*** -1.7*** -1.6*** -0.4*** -0.5*** -0.2*** 0.2***Two Quarters before Quarter t -0.2** -1.1*** -0.8*** -1.2*** -1.8*** -2.1*** -1.1*** -0.4*** -0.2*** 0.2*** 0.2***One Quarter before Quarter t -0.9*** -1.0*** -1.3*** -1.2*** -2.2*** -1.6*** -1.2*** 8.9*** -0.2*** 0.2** 0.2*** 0.1

CAMELS 3 Constant (Eight Quarters before Quarter t) 68.5*** 68.3*** 67.1*** 66.7*** 67.6*** 67.4*** 67.2*** 66.7*** 67.2*** 67.3*** 68.1*** 67.8*** 78.7*** 78.9*** 79.0*** 79.0***

Seven Quarters before Quarter t 0.2 -0.2 0.1 0.8*** 0.2 -0.6*** -0.4*** 0.4** -0.3*** 0.9*** -0.2 0.6***Six Quarters before Quarter t -0.0 -0.0 0.9*** 0.8*** -0.2 -1.0*** -0.0 0.2 0.5*** 0.7*** 0.4** 0.6***Five Quarters before Quarter t 0.5 0.7** 1.1*** 0.8*** -0.6** -0.5* -0.3 1.0*** 0.4** 1.3*** 0.4**Four Quarters before Quarter t 1.1** 1.0*** 1.1*** 0.6* -0.2 -0.8*** 0.6** 0.9*** 1.0*** 1.3*** 0.1Three Quarters before Quarter t 1.2*** 1.2*** 0.8** 0.9** -0.3 0.1 0.6* 1.6*** 1.0*** 0.1 0.7***Two Quarters before Quarter t 1.5*** 0.8** 1.2*** 0.9** 0.6* 0.3 1.4*** 1.7*** 0.1 0.7*** 0.8***One Quarter before Quarter t 1.2** 1.4*** 1.2*** 1.8*** 0.8** 1.4*** 1.7*** 12.1*** 0.2 0.9*** 0.8*** 1.0***

CAMELS 4, 5 Constant (Eight Quarters before Quarter t) 69.7*** 68.9*** 67.7*** 67.0*** 67.0*** 67.1*** 66.0*** 65.2*** 66.0*** 66.0*** 66.8*** 67.2*** 80.7*** 80.5*** 80.2*** 80.2***

Seven Quarters before Quarter t 0.1 -0.1 0.0 1.9*** 0.4 -0.3 -0.7*** 0.4* 0.1 1.2*** 0.3 1.0***Six Quarters before Quarter t 0.7 0.1 2.0*** 2.3*** 0.3 -0.8*** -0.1 0.6* 1.4*** 1.6*** 1.4*** 1.4***Five Quarters before Quarter t 1.1 1.8* 2.1*** 1.8*** -0.1 -0.2 0.3 2.1*** 1.9*** 2.7*** 1.7***Four Quarters before Quarter t 3.4** 2.6** 1.7** 1.7** 0.1 0.5 1.9*** 2.7*** 3.0*** 3.1*** 0.7***Three Quarters before Quarter t 4.4*** 2.1* 1.9** 2.4*** 0.8 2.0*** 2.5*** 3.8*** 3.4*** 0.6*** 1.7***Two Quarters before Quarter t 4.0*** 2.5** 2.4*** 3.3*** 2.6*** 2.8*** 3.5*** 4.4*** 0.6*** 1.6*** 2.3***One Quarter before Quarter t 4.4*** 3.0** 3.7*** 5.1*** 3.2*** 3.6*** 4.1*** 15.7*** 0.8*** 1.6*** 2.3*** 3.1***

Failed Banks Constant (Eight Quarters before Failure) 83.0*** 48.0** 51.6*** 54.0*** 56.5*** 57.6*** 66.2*** 65.0*** 66.5*** 63.8*** 66.8*** 66.6*** 84.8*** 84.1*** 82.7*** 82.0***

Seven Quarters before Failure -0.7 -2.8*** -0.4 3.8 -0.7 3.2 -0.0 -2.5*** 1.0 3.5** 1.2** 0.8Six Quarters before Failure -2.3* -1.6 0.0 4.2 -1.8 2.7 2.3** -3.2* 3.4*** 3.5* 2.4*** 3.1*Five Quarters before Failure -3.0 37.1 1.0 7.5* 3.2 3.1 1.9* -0.4 4.3*** 6.2*** 3.3***Four Quarters before Failure -3.6 36.3 4.9** 7.2* 4.8 4.1 6.8*** 2.9** 5.0*** 6.1*** 1.3Three Quarters before Failure -3.6*** 34.5 10.6** 5.0 5.2 6.2 7.9*** 4.3*** 6.9*** 1.5** 2.8***Two Quarters before Failure -5.0*** 36.1 17.3*** 17.6*** 9.4* 7.9* 9.4*** 6.0*** -0.0 2.4*** 2.3**One Quarter before Failure -2.8 39.3 25.5*** 15.3*** 12.8** 8.8** 9.6*** 17.9*** 1.1* 2.5*** 3.6*** 4.3***

Observations 56,240 56,064 55,880 55,704 55,824 55,880 56,128 55,976 42,024 35,010 28,016 20,853 14,008 21,006 28,016 34,755

Number of Banks 7,030 7,008 6,985 6,963 6,978 6,985 7,016 6,997 7,004 7,002 7,004 6,951 7,004 7,002 7,004 6,951

***=SiR-squared 0.951 0.951 0.950 0.951 0.952 0.952 0.953 0.956 0.954 0.955 0.956 0.956 0.971 0.971 0.972 0.972

gnificantly different from zero at the 99 percent confidence level; **=at 95 percent confidence level; *=at 90 percent confidence level

A

FDIC Claims

ppendix B.1
46

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15) (16)

2008Q1 2008Q2 2008Q3 2008Q4 2009Q1 2009Q2 2009Q3 2009Q4 2010Q1 2010Q2 2010Q3 2010Q4 2010Q1 2010Q2 2010Q3 2010Q4

CAMELS 1,2 Constant (Eight Quarters before Quarter t) 16.0*** 15.4*** 15.4*** 15.9*** 15.5*** 15.0*** 15.1*** 15.4*** 15.3*** 15.3*** 15.1*** 15.8*** 7.6*** 7.6*** 7.7*** 7.7***

Seven Quarters before Quarter t -0.6*** 0.1** 0.6*** -0.2*** -0.2*** 0.1* 0.5*** -0.1* -0.1* -0.2*** 0.6*** 0.4***Six Quarters before Quarter t -0.5*** 0.7*** 0.3*** -0.5*** -0.1** 0.5*** 0.4*** -0.2** -0.4*** 0.4*** 1.0*** 0.5***Five Quarters before Quarter t 0.1 0.5*** 0.1 -0.4*** 0.3*** 0.4*** 0.3*** -0.5*** 0.3*** 0.8*** 1.1***Four Quarters before Quarter t -0.2** 0.2*** 0.2** 0.0 0.2** 0.3*** -0.0 0.1 0.7*** 0.9*** 0.4***Three Quarters before Quarter t -0.4*** 0.3*** 0.6*** -0.1 0.1 -0.0 0.6*** 0.6*** 0.8*** 0.4*** 0.4***Two Quarters before Quarter t -0.4*** 0.7*** 5.6*** -0.2** -0.3*** 0.6*** 6.1*** 0.7*** 0.4*** 5.0*** 0.5***One Quarter before Quarter t 0.1 5.7*** 5.4*** -0.6*** 0.3*** 6.1*** 6.2*** -7.8*** 0.4*** 5.0*** 5.0*** 0.7***

CAMELS 3 Constant (Eight Quarters before Quarter t) 17.5*** 17.9*** 19.9*** 20.9*** 20.6*** 20.8*** 20.2*** 20.0*** 19.3*** 18.5*** 17.5*** 18.1*** 9.9*** 9.7*** 9.6*** 9.6***

Seven Quarters before Quarter t -0.6** 0.4** 0.1 -0.3 -0.4* -0.1 -0.4** -0.6*** -0.5*** -1.1*** 0.5*** 0.6***Six Quarters before Quarter t -0.2 0.5** -0.3 -0.6** -0.6*** -0.4** -1.0*** -1.2*** -1.5*** -0.5*** 1.2*** 1.0***Five Quarters before Quarter t -0.1 0.2 -0.6** -1.1*** -0.9*** -1.0*** -1.6*** -2.2*** -0.9*** 0.2 1.6***Four Quarters before Quarter t -0.3 -0.2 -1.1*** -1.4*** -1.4*** -1.6*** -2.5*** -1.7*** -0.3 0.6*** 0.3***Three Quarters before Quarter t -0.5 -0.7** -1.3*** -1.8*** -2.2*** -2.6*** -2.2*** -1.0*** 0.1 0.4*** 0.4***Two Quarters before Quarter t -1.1** -0.8** 1.9*** -2.6*** -3.0*** -2.5*** 1.7*** -0.7*** 0.3** 3.3*** 0.4***One Quarter before Quarter t -1.1** 2.6*** 1.2** -3.4*** -2.9*** 1.0** 1.9*** -10.2*** 0.3** 3.2*** 3.5*** 0.5***

CAMELS 4, 5 Constant (Eight Quarters before Quarter t) 17.8*** 18.8*** 19.9*** 20.3*** 20.6*** 20.7*** 21.2*** 21.3*** 20.2*** 19.6*** 19.0*** 19.2*** 8.2*** 8.5*** 8.7*** 8.8***

Seven Quarters before Quarter t -0.2 0.3 0.2 -1.5*** -0.7** -0.4* 0.2 -0.8*** -1.0*** -0.9*** 0.1 0.3*Six Quarters before Quarter t -0.8 0.5 -1.3* -2.1*** -1.2*** -0.5 -0.8** -1.9*** -2.0*** -0.9*** 0.5* 0.4*Five Quarters before Quarter t -0.8 -0.7 -1.6** -2.0*** -1.4*** -1.2*** -2.1*** -3.0*** -2.0*** -0.6** 0.6**Four Quarters before Quarter t -2.5* -1.2 -1.3* -2.2*** -1.7*** -2.6*** -3.2*** -3.0*** -1.7*** -0.4 -0.2Three Quarters before Quarter t -3.4** -0.9 -1.5* -3.3*** -2.9*** -3.7*** -3.1*** -2.9*** -1.5*** -0.2 -0.6***Two Quarters before Quarter t -3.2** -1.3 1.2 -4.2*** -4.3*** -3.5*** -0.4 -2.7*** -0.1 1.5*** -0.8***One Quarter before Quarter t -3.7** 1.8 -0.1 -5.6*** -4.0*** -0.7 -0.4 -13.2*** -0.2 1.5*** 1.3*** -1.3***

Failed Banks Constant (Eight Quarters before Failure) 2.3*** 32.3* 24.9*** 31.9*** 30.1*** 27.7*** 21.5*** 20.8*** 20.4*** 22.8*** 20.8*** 20.6*** 6.8*** 6.3*** 8.0*** 8.1***

Seven Quarters before Failure -0.5 -1.0* 1.2 -2.3 0.0 -3.9 -1.1 -0.6 -0.8 -2.9** -0.2 0.6Six Quarters before Failure -0.9 1.8 3.2** -2.4 0.2 -4.8 -2.7*** -0.1 -2.5** -2.8 -0.2 -0.9Five Quarters before Failure -0.4 -27.1 1.7 -7.1 -4.8 -4.9 -2.1* -2.5** -2.9** -4.2** -1.2Four Quarters before Failure 0.8 -26.5 -0.8 -6.3 -6.5 -4.5 -6.6*** -4.1*** -2.0 -3.0* -1.3Three Quarters before Failure -0.6 -23.7 -0.9 -0.8 -7.4 -5.1 -5.9*** -2.1 -3.4** -0.9 -1.3Two Quarters before Failure -0.7 -26.3 -6.8* -13.1*** -11.5** -6.7 -4.0** -2.5 0.8 -0.5 -0.7One Quarter before Failure -0.2 -22.8 -11.8*** -11.2*** -13.6*** -4.1 -3.5* -13.6*** -1.1** -0.6 -1.6* -2.3*

Observations 56,240 56,064 55,880 55,704 55,824 55,880 56,128 55,976 42,024 35,010 28,016 20,853 14,008 21,006 28,016 34,755

Number of Banks 7,030 7,008 6,985 6,963 6,978 6,985 7,016 6,997 7,004 7,002 7,004 6,951 7,004 7,002 7,004 6,951

R-squared 0.586 0.611 0.635 0.604 0.613 0.641 0.665 0.627 0.644 0.645 0.650 0.655 0.410 0.487 0.519 0.416

Appendix B.2

Uninsured Claims

***=Significantly different from zero at the 99 percent confidence level; **=at 95 percent confidence level; *=at 90 percent confidence level
47

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

2008Q1 2008Q2 2008Q3 2008Q4 2009Q1 2009Q2 2009Q3 2009Q4 2010Q1 2010Q2 2010Q3 2010Q4

CAMELS 1,2 Constant (Eight Quarters before Quarter t) 1.0*** 0.9*** 1.0*** 1.7*** 1.6*** 1.7*** 1.8*** 1.8*** 1.7*** 1.8*** 1.8*** 1.8***

Seven Quarters before Quarter t 0.0 0.1*** 0.7*** -0.1*** 0.1*** 0.1*** -0.0 -0.1*** 0.2*** 0.0 -0.1** -0.2***Six Quarters before Quarter t 0.1*** 0.8*** 0.6*** 0.0 0.2*** 0.1*** -0.2*** 0.1* 0.2*** -0.0 -0.2*** -0.1***Five Quarters before Quarter t 0.8*** 0.7*** 0.7*** 0.1*** 0.2*** -0.0 0.0 0.1* 0.1** -0.2*** -0.2*** -0.1**Four Quarters before Quarter t 0.7*** 0.8*** 0.8*** 0.1*** 0.1* 0.2*** 0.1 0.0 -0.1 -0.2*** -0.2*** -0.2***Three Quarters before Quarter t 0.8*** 0.9*** 0.8*** -0.0 0.3*** 0.2*** -0.0 -0.1*** -0.0 -0.2*** -0.3*** -0.3***Two Quarters before Quarter t 0.9*** 0.9*** 0.7*** 0.2*** 0.3*** 0.1* -0.2*** -0.1** -0.0 -0.3*** -0.4*** -0.3***One Quarter before Quarter t 0.9*** 0.8*** 0.9*** 0.2*** 0.2*** -0.1* -0.2*** -0.1* -0.1** -0.4*** -0.3*** -0.2***

CAMELS 3 Constant (Eight Quarters before Quarter t) 0.8*** 0.8*** 0.7*** 1.5*** 1.2*** 1.2*** 1.6*** 1.8*** 1.8*** 1.9*** 1.8*** 1.6***

Seven Quarters before Quarter t 0.1 -0.1 0.8*** -0.1 0.1** 0.1* 0.1** -0.1 0.2*** -0.1 -0.2*** -0.2***Six Quarters before Quarter t -0.0 0.8*** 0.7*** -0.0 0.2*** 0.2*** 0.1 0.1 0.2* -0.3*** -0.4*** -0.3***Five Quarters before Quarter t 0.9*** 0.7*** 0.8*** 0.1 0.3*** 0.1* 0.3*** 0.0 -0.1* -0.5*** -0.6*** -0.4***Four Quarters before Quarter t 0.8*** 0.8*** 0.9*** 0.2** 0.2*** 0.3*** 0.2** -0.2** -0.3*** -0.6*** -0.6*** -0.5***Three Quarters before Quarter t 0.9*** 0.8*** 0.9*** 0.1 0.4*** 0.2*** -0.0 -0.4*** -0.4*** -0.7*** -0.7*** -0.6***Two Quarters before Quarter t 0.9*** 0.8*** 0.8*** 0.3*** 0.3*** 0.0 -0.2*** -0.5*** -0.5*** -0.8*** -0.8*** -0.5***One Quarter before Quarter t 0.9*** 0.7*** 1.1*** 0.2 0.1 -0.1 -0.3*** -0.6*** -0.6*** -0.9*** -0.8*** -0.5***

CAMELS 4, 5 Constant (Eight Quarters before Quarter t) 0.6*** 0.5*** 0.6*** 1.7*** 1.8*** 1.7*** 1.6*** 1.7*** 1.4*** 1.7*** 1.4*** 1.1***

Seven Quarters before Quarter t 0.0 0.0* 0.4*** -0.2 0.1 -0.0 0.1** -0.1 0.2*** -0.3** -0.3** -0.2**Six Quarters before Quarter t -0.0 0.3*** 0.2*** -0.1 0.0 0.2 -0.1 0.1 -0.1 -0.6*** -0.4*** -0.0Five Quarters before Quarter t 0.6** 0.3*** 0.5*** -0.1 0.1 -0.0 0.2** -0.3 -0.4** -0.8*** -0.3*** -0.0Four Quarters before Quarter t 0.4*** 0.3*** 0.4*** -0.1 0.0 0.2 -0.1 -0.6*** -0.5*** -0.6*** -0.3** -0.1*Three Quarters before Quarter t 0.5*** 0.3*** 0.5*** 0.1 0.2 -0.1 -0.5** -0.6*** -0.4*** -0.6*** -0.4*** -0.2***Two Quarters before Quarter t 0.5*** 0.3*** 0.6** -0.1 -0.2 -0.7** -0.5** -0.5*** -0.4*** -0.7*** -0.5*** -0.3***One Quarter before Quarter t 0.9** 0.4** 0.4*** -0.6 -0.8* -0.6** -0.3** -0.5*** -0.5*** -0.8*** -0.5*** -0.3***

Failed Banks Constant (Eight Quarters before Failure) 0.7* 0.8*** 1.2** 0.6*** 0.6*** 3.8 1.3*** 2.7** 1.8** 1.0*** 0.9*** 0.8***

Seven Quarters before Failure 0.0 0.3* 10.1 0.9 0.2 0.5 0.8** 1.2 -0.2 -0.2 -0.3** -0.3*Six Quarters before Failure -0.0 0.0 8.4 0.8** 0.4** 0.4** -0.2 0.4 -0.6 -0.4* -0.4*** -0.2*Five Quarters before Failure 1.0** -0.2*** 9.0 0.4 0.2 0.3 0.1 -0.6 -0.8* -0.2 -0.3* -0.4**Four Quarters before Failure 0.9 1.4 7.5 0.4** 0.2 -0.5 -0.3 -0.9* -1.1 -0.5** -0.3** -0.3Three Quarters before Failure 2.4*** -0.5*** 2.5 0.5 -0.1 -1.0 -0.6*** -1.3** -1.1 -0.5** -0.4** -0.4Two Quarters before Failure 3.9*** -0.2 2.3 0.8 -0.2 -0.2 -0.7*** -1.6* -1.2* -0.5** -0.4*** -0.3One Quarter before Failure 0.5 -0.4** 0.3 -0.2 0.1 -2.0 -0.7*** -1.9* -1.0 -0.4 -0.4** -0.3

Observations 56,240 56,064 55,880 55,704 55,824 55,880 56,128 55,976 56,032 56,016 56,032 55,608Number of Banks 7,030 7,008 6,985 6,963 6,978 6,985 7,016 6,997 7,004 7,002 7,004 6,951R-squared 0.049 0.051 0.055 0.056 0.058 0.058 0.058 0.058 0.057 0.057 0.055 0.053

Appendix B.3

General Creditor Claims

***=Significantly different from zero at the 99 percent confidence level; **=at 95 percent confidence level; *=at 90 percent confidence level