Directory UMM :Data Elmu:jurnal:J-a:Journal Of Banking And Finance:Vol25.Issue2.2001:
Journal of Banking & Finance 25 (2001) 393±417
www.elsevier.com/locate/econbase
The impact of FDICIA on bank returns and
risk: Evidence from the capital markets
Aigbe Akhigbe a, Ann Marie Whyte
b,*
a
b
Florida Atlantic University, Boca Raton FL, USA
Department of Finance, College of Business Administration, University of Central Florida,
P.O. Box 161400, Orlando, FL 32816-1400, USA
Received 12 March 1999; accepted 4 November 1999
Abstract
This study examines the impact of the Federal Deposit Insurance Corporation Improvement Act (FDICIA) of 1991 on bank stock returns and risk. We ®nd that FDICIA
had a generally positive eect on bank stock returns and resulted in a signi®cant reduction in bank risk. The extent of the risk reduction varies based on the capitalization,
size, and credit risk of the institutions with poorly capitalized, large, and high credit risk
banks experiencing the greatest risk reduction. The results obtained using two separate
control groups also bolster the conclusion that FDICIAÕs passage resulted in a significant decline in bank risk. Ó 2001 Elsevier Science B.V. All rights reserved.
JEL classi®cation: G21; G28
Keywords: Bank risk; Wealth eects; Bank regulation
1. Introduction
The passage of the Federal Deposit Insurance Corporation Improvement
Act (FDICIA) in 1991 marked a signi®cant regulatory milestone for the
*
Corresponding author. Tel.: +1-407-823-3945; fax: +407-823-6676.
E-mail addresses: [email protected] (A.M. Whyte).
0378-4266/01/$ - see front matter Ó 2001 Elsevier Science B.V. All rights reserved.
PII: S 0 3 7 8 - 4 2 6 6 ( 9 9 ) 0 0 1 3 1 - 4
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A. Akhigbe, A.M. Whyte / Journal of Banking & Finance 25 (2001) 393±417
banking industry. The act contains several important provisions including
improving the capitalization of the Federal Deposit Insurance Corporation
(FDIC), more stringent capital requirements, early regulatory intervention in
the aairs of troubled or undercapitalized banks, prompt failure resolution,
and risk-based deposit insurance premiums.
This study examines changes in capital market measures of risk for a sample
of bank holding companies (BHCs) and banks following the passage of
FDICIA. A secondary focus of the study is to re-examine the wealth eects
surrounding FDICIAÕs passage. Two previous studies by Madura and Bartunek (1995) and Liang et al. (1996) have examined the wealth eects of
FDICIA. This study complements their work using a larger sample of institutions and expands the analysis to include an examination of the impact of
FDICIA on risk.
Several studies have examined the eects of regulatory intervention on
shareholder wealth. Cornett and Tehranian (1989) examine the wealth eects of
the Depository Institutions Deregulation and Monetary Control Act
(DIDMCA) of 1980 and ®nd that shareholders of large commercial banks
experienced signi®cant positive abnormal returns while shareholders of small
commercial banks and savings and loans (S&Ls) experienced signi®cant negative returns. Cornett and Tehranian (1990) ®nd that the Garn-St. Germain
Depository Institutions Act of 1982 resulted in positive abnormal returns to
shareholders of large S&Ls and commercial banks and negative returns for
small S&Ls and banks. Sundaram et al. (1992) show that the passage of the
Financial Institutions Reform, Recovery, and Enforcement Act (FIRREA) of
1989 resulted in positive abnormal returns for both banks and S&Ls. Alexander
and Spivey (1994) examine the impact of the Competitive Equality Banking Act
(CEBA) of 1987 on the returns of S&Ls and document negative abnormal
returns for well capitalized S&Ls and positive eects for less capitalized S&Ls.
More recently, Madura and Bartunek (1995) and Liang et al. (1996) examine the wealth eects of FDICIA. Madura and Bartunek (1995) use a
sample of 89 institutions and ®nd that small and medium-sized banks were
favorably aected by events surrounding FDICIAÕs passage while large banks
were negatively aected by FDICIA's passage. They also ®nd that banks with
high capital to asset ratios experienced a more favorable share price response.
Liang et al. (1996) use a sample of 164 BHCs and ®nd that the shareholders of
well capitalized banks bene®ted from the enactment of FDICIA while those of
undercapitalized banks experienced signi®cant losses. This is consistent with
Madura and BartunekÕs (1995) ®nding that banks with high capital to asset
ratios reacted more favorably than banks with relatively low capital to asset
ratios. However, while Madura and Bartunek (1995) document a positive reaction for small and medium-sized banks, Liang et al. (1996) ®nd that the
reaction of large and small banks is insigni®cant and statistically indistinguishable. Both studies focus exclusively on the impact of FDICIA on returns,
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395
but do not consider the legislation's impact on bank risk. Since regulators are
concerned with the solvency of the banking system, they are concerned with
both wealth eects and risk changes associated with regulatory intervention.
This study ®lls a gap in the literature by examining changes in bank risk following FDICIA's passage.
Studies focusing on the impact of regulation on bank risk include Mingo
(1978), Koehn and Stangle (1980), Smirlock (1984), Allen and Wilhelm (1988),
Bundt et al. (1992) and Sundaram et al. (1992). Mingo (1978) ®nds that deposit-rate ceilings increase a bank's total risk while Koehn and Stangle (1980)
®nd that systematic risk is not aected by deposit rate ceilings. Smirlock (1984)
provides evidence that the deregulation of deposit rates resulting from the
passage of the DIDMCA of 1980 had no impact on systematic or unsystematic
risk. Similar ®ndings are documented by Allen and Wilhelm (1988). However,
Aharony et al. (1988) ®nd that DIDMCA's passage resulted in an increase in
total risk for both money center and regional banks but a decrease in total risk
for thrifts. More recently, Bundt et al. (1992) provide evidence that DIDMCA's passage resulted in increases in both systematic and unsystematic
measures of bank risk. Sundaram et al. (1992) show that the passage of the
FIRREA of 1989 increased the risk of both banks and S&Ls. Finally, Alexander and Spivey (1994) ®nd that less capitalized institutions experienced a
signi®cant decrease in risk following CEBAÕs passage.
Overall, these studies provide ample precedent for the proposition that
regulation can potentially impact both shareholder wealth and risk. Furthermore, they suggest that the impact is likely to be dependent on factors such as
bank size and capitalization. Accordingly, this study examines the impact of
FDICIA on shareholder wealth and bank risk. Previous studies by Madura and
Bartunek (1995) and Liang et al. (1996) have already demonstrated that
FDICIA's provisions resulted in signi®cant wealth eects for bank shareholders. We add to these studies by using a broader sample of institutions and
examining the impact on bank risk. FDICIA's passage may have contributed to
a change in bank risk since several key provisions of the legislation are aimed at
promoting stability and discouraging excessive risk taking in the banking industry. For example, the imposition of more stringent capital requirements
should reduce bank risk, particularly in the case of poorly capitalized banks.
Similarly, the introduction of risk-based insurance premiums imposes market
discipline and should reduce risk-taking behavior on the part of banks.
The seemingly unrelated regression (SUR) model is used to assess the wealth
eects of FDICIA. The risk shift analysis is conducted using several capital
market measures of risk; total, systematic, interest rate, and unsystematic risks.
The study utilizes a methodology similar to that employed by Smirlock (1984),
and Aharony et al. (1986, 1988). The methodology estimates several capital
market measures of risk over a pre- and post-FDICIA period for several equallyweighted portfolios of banks based on capitalization, size, and credit risk.
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A. Akhigbe, A.M. Whyte / Journal of Banking & Finance 25 (2001) 393±417
The empirical evidence is consistent with the proposition that the wealth
eects of FDICIA are generally positive. Furthermore, the evidence shows that
the institutions experienced a signi®cant reduction in total, systematic, and
unsystematic risk following FDICIAÕs passage, and the results vary based on
the capitalization, size, and credit risk of the institutions. In particular, we ®nd
that poorly capitalized, large, and high credit risk banks experience the greatest
reduction in risk. The results for two separate control groups provide further
support for the conclusion that the observed reduction in bank risk is attributable to FDICIAÕs passage and not to economy-wide forces. In contrast, there
is no evidence of a signi®cant change in interest rate risk in the wake of
FDICIAÕs passage. This result is not surprising since FDICIA does not explicitly address interest rate risk. Consequently, banks are not motivated to
alter their interest rate exposure in the wake of FDICIAÕs passage. Overall, the
®ndings support a signi®cant reduction in risk in the banking industry following the passage of FDICIA.
These ®ndings have important implications for regulators and shareholders.
Regarding regulators, it appears that FDICIAÕs provisions including riskbased capital requirements, risk-based insurance premiums, limited discount
window access, and prompt corrective action had the desired eect on bank
risk. Regarding stockholders, the results suggest that well diversi®ed shareholders should reduce their required rates of return on bank stocks in the wake
of FDICIAÕs passage.
The remainder of the paper is organized as follows. First, hypotheses related
to key provisions are developed and the possible implications for changes in
bank risk are presented. Next, the data and methodology are detailed and the
results are discussed. Finally, the conclusions are presented and the implications are oered.
2. Hypotheses related to key provisions of FDICIA
This section outlines key provisions of FDICIA and the possible implications for bank risk. 1 From an investment standpoint, stockholders who hold
well-diversi®ed portfolios are only concerned with the systematic risk of an
institution. Thus, if FDICIAÕs passage does not impact systematic risk,
stockholders should be indierent to this type of regulation. If, however,
1
Since the wealth eects already been examined in previous studies, this section focuses on
hypotheses related to the implications of FDICIA for bank risk in the interest of brevity. In
general, the emphasis of the law on promoting safety and soundness should be good news for the
banking industry as a whole and may result in positive wealth eects. It is possible, however, that
some provisions, including higher insurance premiums, may result in negative wealth eects.
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397
FDICIAÕs passage reduces systematic risk, stockholders should reduce their
required returns accordingly. From a regulatory standpoint, the total risk of an
institution is relevant, not just systematic risk (Mingo, 1978). Peltzman (1976)
argues that regulation alters the riskiness of the regulated ®rm by lowering the
variability of earnings which should reduce both systematic and unsystematic
risks. Accordingly, this study examines the impact of FDICIAÕs passage on
total, systematic, and unsystematic risks and, as such, provides implications for
both stockholders and regulators.
Several key provisions of FDICIA are likely to contribute to a signi®cant
change in bank risk. Based on the literature review and the evidence provided
by Madura and Bartunek (1995) and Liang et al. (1996) for the wealth eects of
FDICIA, the legislationÕs impact on risk may vary with bank capitalization
and size. Thus, the hypotheses are developed for each provision based on bank
capitalization and size. We also examine whether the risk changes vary based
on the credit risk of the institutions.
2.1. Improving the capitalization of the FDIC
FDICIA provided a temporary injection of an additional $30 billion into the
FDIC. Under FDICIA, permanent capitalization of the FDIC is provided by
the deposit insurance premiums paid by banks. This improved capitalization
may have conveyed a positive signal to the market and may have reduced the
marketÕs perception of risk since the FDIC is now better positioned to handle
losses in the event that a failure occurs. This argument suggests that all banks,
irrespective of capitalization, size, or credit risk, may experience an overall
reduction in risk.
2.2. Prompt corrective action
FDICIA re¯ects a shift in emphasis from regulatory forbearance to prompt
corrective action in the case of undercapitalized banks. With prompt corrective
action, banks face stringent regulatory measures and the threat of closure if they
become undercapitalized. Dahl and Spivey (1995) argue that prompt corrective
action should reduce losses in at least three ways. First, prompt corrective action may lower the resolution costs for undercapitalized banks which ultimately
fail by limiting the length of time a bank is undercapitalized prior to failure.
Second, prompt corrective action should discourage healthy banks from becoming undercapitalized. Third, prompt corrective action may reduce the
number of failures of undercapitalized banks, thereby reducing the resolution
costs borne by the FDIC. These arguments suggest that poorly capitalized
banks should experience a signi®cant reduction in risk as they are forced to
improve their capitalization. The impact may also vary based on bank size.
Madura and Bartunek (1995) argue that large banks tend to have lower capital
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A. Akhigbe, A.M. Whyte / Journal of Banking & Finance 25 (2001) 393±417
to asset ratios and to invest in riskier assets than small banks since they are more
diversi®ed. To the extent that FDICIA threatens early intervention, large,
poorly capitalized banks should have an incentive to decrease their risk-taking
activities. Similarly, banks with high credit risk and low capital to asset ratios
should also have an incentive to reduce risk to avoid the threat of early closure.
2.3. Discount window access
FDICIA limits the access of undercapitalized banks to the discount window,
eectively curtailing the ability of these institutions to boost short-term liquidity by borrowing from the discount window. This provision should serve
as an incentive for undercapitalized banks to quickly improve their capital
positions or face closure by regulatory authorities. The same incentive should
exist regardless of size since both large and small banks would have limited
access to the discount window if they become signi®cantly undercapitalized.
High credit risk banks would also have an incentive to reduce risk since they
can no longer rely on the discount window to provide temporary liquidity.
2.4. Too-big-to-fail doctrine
FDICIA eectively eliminates the too-big-to-fail doctrine (Wall, 1993). The
act prohibits the FDIC from protecting deposits above the maximum insurance
limit, and provides that exceptions can only be made by agreement of the
FDIC, the Federal Reserve, and the Treasury. This provision may increase the
perceived riskiness of large banks since the FDIC will only provide limited
coverage in the event of failure. On the other hand, large banks now have an
incentive to reduce risk since they can no longer rely on the FDIC to rescue
them or to protect uninsured depositors. Thus, de jure uninsured depositors
who are aware of this change now have an incentive to monitor the activities of
banks thereby limiting the risk-taking activities of banks. Large banks may,
therefore, experience a reduction in risk following FDICIAÕs passage.
2.5. Risk-based deposit insurance premiums
FDICIA mandates risk-based deposit insurance premiums, with undercapitalized banks being forced to pay higher insurance premiums than well capitalized banks. This provision reduces the moral hazard problem and should
encourage banks to reduce excessive risk-taking since they will ultimately be
penalized with higher insurance premiums. Based on this provision, high risk
banks (poorly capitalized and or high credit risk banks) should experience a
signi®cant reduction in risk.
Overall, FDICIAÕs provisions suggest that banks should experience a signi®cant change in risk following the lawÕs passage. In particular, banks should
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399
experience a reduction in risk in the post-FDICIA era relative to the preFDICIA era.
3. Data and methodology
The eects of FDICIA on shareholder wealth and bank risk are examined
using daily common stock returns for BHCs and banks over the period surrounding FDICIAÕs passage. The sample is constructed by identifying all institutions on the Center for Research in Security Prices (CRSP) tapes with 602,
603 or 671 as the standard industry classi®cation (SIC) code, and which have
returns for 300 trading days in the pre- and post-event periods. After generating this list, the MoodyÕs Bank and Finance Manual for 1991 is used to verify
that the listed institutions are indeed BHCs or banks. This procedure resulted
in a ®nal sample of 322 BHCs and banks.
As with most regulations, the legislative process surrounding FDICIAÕs
passage was complex and involved the announcement of various events leading
up to the ®nal passage of the law. Table 1 identi®es the date of each event and
provides a brief description. The event dates and descriptions are obtained
from Table 1 of the Liang et al. (1996) study and are presented here to provide
clarity in interpreting the results.
The SUR model is used to estimate the share price response of the bank
portfolios. Johnston (1984) argues that in the presence of contemporaneous
correlation the SUR methodology generates more ecient estimates. The
model is estimated as
Rpt ap bmp Rmt bip Rit
9
X
cpk Dk ept ;
1
k1
where Rpt is the return on the bank portfolio on day t, ap the intercept term, bmp
measures market/systematic risk of the portfolio, Rmt the return on the CRSP
equally-weighted market portfolio on day t, bip measures interest rate risk of
the portfolio, Rit the daily change in the interest rate on the 30 year Treasury
bond, 2 cpk measures the sensitivity of the portfolio to event k, Dk a dummy
variable equal to 1 for the kth event date and 0 otherwise, ept is the disturbance
term on the portfolio on day t.
Eq. (1) is estimated using daily returns for all trading days in 1991. The
model is estimated for all banks and several additional bank portfolios based
2
Kane and Unal (1988) note that bank and S&L stock returns are not responsive to short rates
but long rates have a signi®cant eect (Unal and Kane, 1987). Thus, following their methodology,
this paper uses the returns on long-term government bonds to proxy the unanticipated changes in
the interest rate index.
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Table 1
Events surrounding the passage of FDICIAa
Event
Date
Event description
D1
1/2/91
D2
6/5/91
D3
8/5/91
D4
1/7/91
D5
5/11/91
D6
7/11/91
D7
22/11/91
D8
27/11/91
D9
20/12/91
FDIC chairman says the Bank Insurance Fund needs cash infusion of up
to $10 billion
The Federal Reserve Bank opposes an important provision in the bill
that could restrict its ability to provide liquidity to troubled banks
The House Financial Institutions Subcommittee approves a bill requiring
regulators to intervene quickly in the aairs of weak banks. The bill also
improves the insurance fund and imposes new auditing standards on
banks
House Banking Committee votes to accept most of the Bush AdministrationÕs proposals to restructure banking laws
House defeats banking bill but the House Banking Committee is
expected to rewrite the bill
House Banking Committee passes a scaled down version of the banking
bill
House and Senate pass separate bills which provide a $70 billion line of
credit to the FDIC and impose new regulations aimed at reducing bank
failures
House accepts Senate provision requiring banks to repay (through higher
insurance premiums) a $30 billion line of credit over a 15 year period
President signs FDICIA into law
a
This table shows the nine event dates and a brief description of each event surrounding FDICIA's
passage. The event dates and descriptions are obtained from the study by Liang et al. (1996).
on capitalization (well capitalized, moderately capitalized, and poorly capitalized banks), size (large, medium-sized, and small banks), and credit risk
(high, moderate, and low credit risk banks). The data on capitalization, size,
and credit risk are obtained from the Bank Condition and Income database on
the Federal Reserve Bank of ChicagoÕs web site. The data from the Bank
Condition and Income reports are matched to the original sample of 322 banks
using the Moody's Bank and Finance Manual for 1991.
The impact of FDICIA on risk is estimated using the methodology outlined
by Aharony et al. (1986, 1988) and Smirlock (1984). The risk measures are
estimated over a short-term interval and a long-term interval. The short-term
interval includes 100 trading days prior to the event period and 100 trading
days after the event period. The long-term interval includes 300 trading days
prior to the event period and 300 trading days after the event period. Recognizing that the numerous announcements leading up to FDICIAÕs passage may
alter the marketÕs expectations, we de®ne the pre-event period as the interval
preceding the ®rst announcement (D1 ) on 1 February 1991 that the chairman
of the FDIC stated that the Bank Insurance Fund (BIF) needed a signi®cant
cash infusion. Similarly, the post-event period is de®ned as the interval following the last news announcement that the bill had been signed into law on
A. Akhigbe, A.M. Whyte / Journal of Banking & Finance 25 (2001) 393±417
401
December 20, 1991 (D9 ). The capital market measures of risk are obtained
using the two-index model which has been utilized extensively in the banking
literature: 3
Rpt ap bmp Rmt bip Rit ept ;
2
where the parameters are as previously de®ned in Eq. (1).
One potential problem in using the two-index model is the need to specify
the relationship between the interest rate change and the market return. Some
studies have dealt with this problem using orthogonalization (Chance and
Lane, 1980; Flannery and James, 1984b). However, as noted by Giliberto
(1985) and Kane and Unal (1988) the orthogonalization procedures produce
biased t-tests. Thus, following Kane and Unal (1988) this study uses the unorthogonalized two-index model. 4 Based on Eq. (2) the variance of the return
on the portfolio is given by
Var Rp b2mp Var Rm b2ip Var Ri Var ep ;
3
where Var is the variance operator. The terms Var Rm and Var Ri re¯ect
market wide factors, whereas b2mp , b2ip , and Var ep are aected by portfolio
speci®c characteristics. Thus, changes in the variance of bank returns Var Rp
could be due to changes in market risk b2mp Var Rm , interest rate risk
b2ip Var Ri , or unsystematic risk Var ep . 5
3
See, for example (Flannery and James, 1984a,b; Aharony et al., 1986, 1988).
To provide further justi®cation for using the unorthogonalized two-index model, Eq. (1) is reestimated as follows. First, the following equation is estimated: Rit apt bim Rmt ept . Then, the
residuals from the equation are substituted into Eq. (1) for the interest rate index (Chance and
Lane, 1980; Aharony et al., 1986). The results using the orthogonalized model are qualitatively
similar to those obtained using the unorthogonalized model. Hence, the results for the
unorthogonalized model are reported. The complete results are available from the authors.
5
Eq. (3) implicitly assumes independence between the interest rate series Rit and the market
return Rmt . To determine whether a covariance term needs to be included in the equation, Eq. (3)
is re-estimated as
4
Var Rp b2mp Var Rm b2ip Var Ri 2bmp bip Cov Rm Ri Var ep :
In all instances, inclusion of the covariance term did not materially alter the variance estimates. For
example, in the pre-FDICIA short-term period for the portfolio of all banks, the covariance term is
calculated as: 2 1:0109 0:0042 ÿ0:000019 0:0000002. Addition of this result to the original
variance estimate of 0.000068 results in no signi®cant change. Further con®rmation of this result is
obtained by using the orthogonalized model described in Footnote 4. The variance estimates are
then obtained using the orthogonalized model and the results are qualitatively similar to the estimates based on Eq. (3). Thus, the variance estimates reported in the paper are based on estimating
Eq. (3). All results are available from the authors.
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The following hypotheses (H) are tested for the sample of all banks:
H1
H2
H3
H4
There is no signi®cant dierence in total risk in the pre-and postFDICIA era for the equally-weighted portfolio of all banks.
There is no signi®cant dierence in systematic risk in the pre-and
post-FDICIA era for the equally-weighted portfolio of all banks.
There is no signi®cant dierence in interest rate risk in the pre-and
post-FDICIA era for the equally-weighted portfolio of all banks.
There is no signi®cant dierence in unsystematic risk in the pre-and
post-FDICIA era for the equally-weighted portfolio of all banks.
The hypotheses are also tested for several subsamples based on capitalization,
size, and credit risk. 6
The analysis is also conducted for two separate control groups. The analysis
of control groups is necessary because during the period surrounding FDICIAÕs passage, a number of events occurred that may have had an impact on
bank risk. First, Berger (1995) argues that banks were generally riskier in the
1980s but raised capital above optimal levels in the early 1990s because of
regulatory changes and unexpectedly high earnings. Second, the Federal Reserve had taken steps to counteract the economic recession and improve bank
capitalization such as reducing the reserve requirements in 1990 (Cosimano
and McDonald, 1998). Finally, the overall economic recovery may have contributed to a decrease in bank risk independent of FDICIA.
To test whether the changes in risk documented for the sample of banks are
most likely attributable to FDICIA and not to these other factors, the above
analysis is repeated for two dierent control samples; ®nance companies and real
estate investment trusts (REITs). Finance companies are in the same line of
business as banks on the asset side of their balance sheet, but are not subject to the
provisions of FDICIA since they do not hold deposits. Similarly, REITs would
be subject to the same real estate problems as banks but would not be subject to
the provisions of FDICIA. Thus, both ®nance companies and REITs represent
the best pool of ®rms for constructing control samples. The sample of ®nance
companies and REITs is obtained from the list provided in volume two of the
Moody's Bank and Finance Manual for 1991. The list is then used to identify those
®nance companies and REITs which are publicly traded and for which return
data are available on CRSP over the sample period. This procedure resulted in a
®nal sample of 93 ®nance companies and 85 REITs. Since the provisions of
FDICIA do not apply to these ®rms, they should not experience a signi®cant
6
The analysis was also conducted for three portfolios formed on the basis of the interest rate risk
of the individual banks prior to FDICIA (high, moderate, and low interest rate risk). The results
were relatively uniform across the three groups. Thus, the risk reduction following FDICIA did not
vary much based on the interest rate risk of the institutions. The complete results are available from
the authors.
A. Akhigbe, A.M. Whyte / Journal of Banking & Finance 25 (2001) 393±417
403
reduction in risk following FDICIAÕs passage. Thus, the results of the control
samples will enable us to determine whether the observed changes in bank risk
are most likely attributable to FDICIAÕs passage.
4. Results
Table 2 provides a summary of the sample characteristics based on data
obtained from the Bank Condition and Income database. The table shows the
sample size and the mean and median capital to asset ratio, total assets, and
nonperforming loans to total assets for the sample banks over the three year
period prior to FDICIAÕs passage. The sample is partitioned into thirds for
each variable; upper third, middle third, and lower third. The full sample
consists of 322 institutions and the upper, middle, and lower thirds have 108,
107 and 107 institutions, respectively. The mean (median) capital to asset ratio
is 7.86 (7.28)% for all banks, 10.45 (9.42)% for the upper third (well capitalized
Table 2
Sample characteristics for all banks and portfolios based on capitalization, size, and credit riska
All banks
Well capitalized banks
Moderately capitalized banks
Poorly capitalized banks
All banks
Large banks
Medium-sized banks
Small banks
All banks
High credit risk banks
Moderate credit risk banks
Low credit risk banks
Mean capital to
asset ratio (%)
Median capital to
asset ratio (%)
Sample size
7.86
10.45
7.26
5.90
7.28
9.42
7.29
6.00
322
108
107
107
Mean total
assets (in billions
of dollars)
Median total assets
(in billions of
dollars)
Sample size
5.40
14.92
1.01
0.26
0.82
6.56
0.82
0.25
322
108
107
107
Mean nonperforming loans/
total assets (%)
Median nonperforming loans/total
assets (%)
Sample size
1.08
5.13
1.08
0.24
322
108
107
107
3.65
9.60
1.09
0.25
a
This table shows the mean and median capital to asset ratio, total assets, and credit risk (measured
as the ratio of nonperforming loans to total assets) for the sample of institutions over the three year
period prior to FDICIAÕs passage. The sample is partitioned into the upper, middle, and lower
third for each variable. The sample includes all banks for which return data are available on CRSP
for the full sample period and for which data are available on the FDICÕs Bank Income and
Condition Reports for the three years prior to FDICIA.
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A. Akhigbe, A.M. Whyte / Journal of Banking & Finance 25 (2001) 393±417
banks), 7.26 (7.29)% for the middle third (moderately capitalized banks) and
5.90 (6.0)% for the lower third (poorly capitalized banks). The mean total
assets for the sample of 322 banks is $5.4 billion while the median is $0.82
billion. The upper third (large banks) has mean (median) total assets of $14.92
billion ($6.56 billion), the middle third (medium-sized banks) has $1.01 billion
(0.82 billion) while the lower third (small banks) has total assets of $0.26 billion
($0.25 billion). Finally, the mean (median) ratio of nonperforming loans to
total assets for all banks is 3.65 (1.08)%, 9.60 (5.13) for the upper third (high
credit risk banks), 1.09 (1.08) for the middle third (moderate credit risk banks)
and 0.25 (0.24) for the lower third (low credit risk banks).
Table 3 shows the share price response of the bank portfolios to the events
surrounding FDICIAÕs passage. The portfolio of all banks reacted positively
(return of 0.8%) to the news that the chairman of the FDIC stated that the BIF
needed an infusion of up to $10 billion (D1 ). The same positive pattern is observed for the portfolios of poorly capitalized, moderately capitalized, and medium-sized banks although the portfolio of poorly capitalized banks is only
marginally signi®cant at the 10% level. Overall, the portfolios do not experience a
signi®cant reaction to the events D2 through D8 . The ®nal event D9 , results in a
positive reaction for the portfolio of all banks (return of 0.9%) and the portfolio
of poorly capitalized banks (return of 1.7%). The portfolio of large banks also
experienced a return of 1.3% which is statistically signi®cant at the 10%. Overall,
the results suggest that the news that the BIF would receive an infusion of up to
$10 billion was good news for banks as was the ultimate passage of FDICIA (D9 ).
This suggests that the provisions of FDICIA aimed at improving the safety and
soundness of the banking system had a positive impact on bank stocks.
Our results contrast with those documented by Liang et al. (1996). They report that banks reacted adversely to D1 . In contrast, we ®nd that most portfolios
reacted favorably to D1 . They document a positive reaction to D4 (the news that
the House Banking Committee voted to accept most of the provisions of FDICIA) while we ®nd no signi®cant reaction to that event. They argue that this
positive reaction suggests that some provisions of FDICIA were good news, on
average, for the banking industry. Finally, we document a positive reaction to
D9 while they ®nd no signi®cant reaction. Overall, we document a positive reaction to FDICIA while they document both positive and negative wealth effects. The dierence in results may arise because we use a comprehensive sample
of 322 BHCs and banks while they use a sample of 164 BHCs. 7 Our results are
7
We include the interest rate index in Eq. (1) while Liang et al. (1996) do not. To ensure that the
dierences in results are not driven by the use of a slightly dierent model, we re-estimate our
results using the model utilized in their study. Overall, the results are qualitatively similar to those
obtained using the two-index model. Thus, the results using the two-index model are reported to be
consistent with the risk shift methodology.
405
A. Akhigbe, A.M. Whyte / Journal of Banking & Finance 25 (2001) 393±417
Table 3
Wealth eects of FDICIA
Rpt ap bmp Rmt bip Rit
9
X
cpk Dk ept
1
k1
Bank portfolios
Market
model
parameters
All
banks
Well
capitalized
banks
Moderately
capitalized
banks
Poorly
capitalized
banks
Large
banks
Medium-sized
banks
Small
banks
ap
0.002
(1.508)
0.869
(28.941)
)0.023
()1.842)
0.008
(2.027)
0.001
(0.090)
)0.002
()0.427)
)0.003
()0.659)
)0.002
()0.560)
)0.001
()0.145)
0.002
(0.373)
0.002
(0.468)
0.009
(2.197)
0.697
0.688
0.003
(1.938)
0.681
(17.767)
)0.035
()2.222)
0.002
(0.399)
)0.006
()1.239)
0.001
(0.209)
)0.004
()0.790)
)0.001
()0.074)
)0.002
()0.406)
0.006
(1.185)
0.002
(0.445)
0.002
(0.448)
0.468
0.453
0.002
(1.759)
0.75
(21.513)
)0.026
()1.797)
0.009
(2.075)
0.009
(1.949)
)0.001
()0.083)
)0.002
()0.468)
)0.004
()0.803)
)0.004
()0.773)
)0.001
()0.078)
)0.004
()0.954)
0.007
(1.470)
0.566
0.553
0.001
)0.03
1.176
(21.439)
)0.008
()0.354)
0.012
(1.733)
)0.001
()0.164)
)0.006
()0.794)
)0.002
()0.219)
)0.003
()0.359)
0.004
(0.537)
)0.001
()0.159)
0.007
)1.036
0.017
(2.333)
0.559
0.546
0.001
)0.722
1.301
(25.026)
)0.027
()1.247)
0.009
)1.288
)0.001
()0.178)
)0.004
()0.567)
0.001
(0.092)
)0.001
()0.022)
)0.004
()0.585)
)0.005
()0.671)
)0.003
()0.471)
0.013
(1.883)
0.631
0.62
0.002
)1.612
0.674
(16.667)
)0.0271
()1.626)
0.015
(2.833)
)0.002
()0.299)
)0.001
()0.249)
)0.008
()1.501)
0.001
(0.099)
0.003
(0.601)
0.001
(0.115)
0.002
(0.436)
0.006
(1.095)
0.447
0.431
0.001
)0.71
0.61
(12.583)
)0.015
()0.740)
)0.001
()0.084)
0.004
(0.643)
0.001
(0.049)
)0.001
()0.038)
)0.007
()1.167)
)0.001
()0.118)
0.009
(1.401)
0.007
(1.059)
0.007
(1.107)
0.305
0.285
81.343
31.076
46.038
44.792
60.414
28.541
15.489
bmp
bip
D1
D2
D3
D4
D5
D6
D7
D8
D9
R2
Adjusted
R2
F-Value
Number of
banks
*
322
108
Signi®cant at the 10% level.
Signi®cant at the 5% level.
***
Signi®cant at the 1% level.
**
107
107
108
107
107
406
A. Akhigbe, A.M. Whyte / Journal of Banking & Finance 25 (2001) 393±417
consistent with Madura and Bartunek's (1995) ®nding that medium-sized banks
reacted favorably to the announcement of the bank reform proposal but are
inconsistent with their ®nding that large banks reacted negatively. It should be
noted, however, that Madura and Bartunek (1995) use a sample of 89 banks and
use slightly dierent event dates than those in this study and in Liang et al.
(1996). 8
The major contribution of this study is the examination of the impact of
FDICIA on bank risk. The results of this analysis are presented in Tables 4±7.
Table 4 shows the change in the variance of the portfolio returns surrounding
FDICIAÕs passage. The signi®cance of the changes in total risk is tested using
an F-statistic under the null H that the variance of returns is equal in the preand post-FDICIA periods. The portfolio of all banks experienced a signi®cant
reduction in total risk in both the short- and long-term intervals. Over the
short-term interval the variance declines by approximately 62% (from 0.000068
to 0.000026) and over the long-term interval by 37% (from 0.000038 to
0.000024). In both instances the reduction is signi®cant at the 1% level. While
most of the other bank portfolios experience a signi®cant decline in risk, the
reduction is most dramatic for the portfolios of poorly capitalized, large, and
high credit risk banks. Poorly capitalized banks experience a decline of 60%
(0.000171±0.000068) and 40% (0.000086±0.000052) in the short- and long-term
intervals, respectively, compared to a decline of 47% (0.000058±0.000031) and
0% (0.000033±0.000033) in the same intervals for well capitalized banks.
Similarly, large banks experience a decline of 68% (0.000191±0.000061) and
55% (0.000099±0.000045) for the short- and long-term intervals, respectively,
while small banks experience a decline of 30% (0.000115±0.000081) and an
increase of 62% (0.000065±0.000105) in the same intervals. Finally, high credit
risk banks experience a decline of 68% (0.000146±0.000047) and 51%
(0.000075±0.000037) in the short- and long-term intervals, respectively, while
low credit risk banks experience declines of 47% (0.000053±0.000028) and 15%
(0.000033±0.000028) in the same intervals. It is interesting to note that the
variance of the market portfolio also declines during the same period. Over the
short-term interval, the variance of the market portfolio declines from 0.000051
to 0.000035 (a decline of 31%) and from 0.000041 to 0.000026 (a decline of
37%) over the long-term interval. Thus, the decline in total risk is partly related
to the decline in the variance of market index over the same period. It is also
8
It should also be noted that it is dicult to compare the results for the portfolios across studies
because of diering de®nitions based on size and capitalization. For example Liang et al. (1996)
de®ne large banks as banks having at least $300 million in total assets while small banks have less
than $300 million in assets. This resulted in a sample of 152 large BHCs and only 12 small BHCs in
their study. Madura and Bartunek (1995) use the following de®nitions: large banks (total assets
greater than $15 billion), medium-sized banks (total assets between $2 and 15 billion) and small
banks (less than $2 billion).
A. Akhigbe, A.M. Whyte / Journal of Banking & Finance 25 (2001) 393±417
407
Table 4
Estimates of shifts in the variance of portfolio returns (Var Rp ) by bank capitalization, size, and
credit risk and estimates of shifts in (Var Rm ) and (Var Ri )a
Portfolio
Pre-FDICIA
Post-FDICIA
F-statistic
All banks
Short-term
Long-term
0.000068
0.000038
0.000026
0.000024
2.61
1.61
Well capitalized banks
Short-term
Long-term
0.000058
0.000033
0.000031
0.000033
1.85
1.01
Moderately capitalized banks
Short-term
Long-term
0.000059
0.000037
0.000025
0.000028
2.32
1.34
Poorly capitalized banks
Short-term
Long-term
0.000171
0.000086
0.000068
0.000052
2.52
1.66
Large banks
Short-term
Long-term
0.000191
0.000099
0.000061
0.000045
3.13
2.21
Medium-sized banks
Short-term
Long-term
0.000062
0.000036
0.000030
0.000027
2.04
1.31
Small banks
Short-term
Long-term
0.000115
0.000065
0.000081
0.000105
1.42
1.63
High credit risk banks
Short-term
Long-term
0.000146
0.000075
0.000047
0.000037
3.13
2.01
Moderate credit risk banks
Short-term
Long-term
0.000084
0.000048
0.000057
0.000056
1.48
1.16
Low credit risk banks
Short-term
Long-term
0.000053
0.000033
0.000028
0.000028
1.89
1.18
Finance companies
Short-term
Long-term
0.000118
0.000077
0.000143
0.000108
1.22
1.41
REITs
Short-term
Long-term
0.000068
0.000043
0.000052
0.000072
1.31
1.67
Market portfolio
Short-term
Long-term
0.000051
0.000041
0.000035
0.000026
1.48
1.60
408
A. Akhigbe, A.M. Whyte / Journal of Banking & Finance 25 (2001) 393±417
Table 4 (Continued)
Portfolio
Pre-FDICIA
Post-FDICIA
F-statistic
Interest rate index
Short-term
Long-term
0.000374
0.000313
0.000349
0.000286
1.07
1.09
a
The short-term impact of FDICIA on total risk is assessed by computing the portfolio variance
over a 100 day pre- and post-event short-term period while the long-term impact is assessed using a
300 day pre- and post-event period. The F-statistics for the variances are based on (99,99) degrees
of freedom in the numerator and denominator, respectively, for the short-term period and
(299,299) degrees of freedom for the long-term analysis. F-statistics are calculated under the null
hypothesis that the variances in the pre- and post-FDICIA period are equal and are calculated as
Var(Group A)/Var(Group B). In all cases Group A refers to the group with the larger variance and
Group B refers to the group with the smaller variance.
*
Signi®cant at the 10% level.
**
Signi®cant at the 5% level.
***
Signi®cant at the 1% level.
interesting to note that the variance of the interest rate index does not change
signi®cantly during the same period.
The results for the control group of ®nance companies show an increase in
the variance of the portfolio returns in the short-term but the change is
insigni®cant. Over the long-term interval, however, the variance actually increases by 40% (from 0.000077 to 0.000108) and the increase is statistically
signi®cant at the 1% level. Similar results are documented for the control
sample of REITs. Although the variance decreases in the short-term the decline
is statistically insigni®cant. Over the long-term interval, however, the variance
increases and the increase is signi®cant at the 1% level. This result is the opposite of that which is observed for the bank portfolios and provides preliminary evidence that the decline in bank risk is most likely attributable to
FDICIAÕs passage.
To identify the change in systematic risk following FDICIAÕs passage, the
change in the market beta and the interest rate beta are also examined. These
risk measures are particularly important to stockholders who hold well-diversi®ed portfolios. The F-statistic is used to test the signi®cance of the changes
under the null H that the coecients are equal in both periods. The results are
shown in Table 5. The market beta for all banks declines from 1.0109 to 0.6787
(a decline of 33%) over the short-term period and from 0.8035 to 0.7161 (a
decline of 11%) in the long-term period. In both instances, the decline is statistically signi®cant. The portfolios based on capitalization show a reduction in
risk in either the short- or long-term interval or both. However, the portfolios
based on size show greater variation in the results. While large banks experience a signi®cant reduction in risk in the short-term, small and medium-sized
banks experience no signi®cant change in risk. The portfolios based on credit
risk also provide some interesting insights. High credit risk banks experience
the most dramatic and consistent decline in systematic risk in both short- and
Table 5
Regression estimates of market (bmp ) and interest rate risk (bip ): pre- and post-event results by bank capitalization, size, and credit riska
All banks
Short-term
Long-term
Well-capitalized banks
Short-term
Long-term
Moderately capitalized banks
Short-term
Long-term
Poorly capitalized banks
Short-term
Long-term
Large banks
Short-term
Long-term
Time interval
(bmp )
t-Statistic
Pre
Post
Pre
Post
1.0109
0.6787
0.8035
0.7161
17.854
12.568
25.887
19.302
Pre
Post
Pre
Post
0.7922
0.5235
0.6264
0.5831
10.898
6.551
16.735
10.281
Pre
Post
Pre
Post
0.8144
0.5113
0.7195
0.6033
11.676
7.776
20.185
12.446
Pre
Post
Pre
Post
1.4549
1.0067
1.0700
0.9670
12.783
10.409
18.839
15.977
Pre
Post
Pre
Post
1.5678
0.9180
1.2013
0.9058
13.532
9.455
20.968
16.217
F-Statistic
18.032
3.267
6.189
0.405
9.999
3.732
9.007
1.541
18.475
0.654
(bip )
t-Statistic
0.0042
0.0226
0.0040
0.0154
0.202
1.329
0.353
1.381
0.0158
)0.0345
0.0086
0.0089
0.586
)1.371
0.634
0.524
)0.0265
0.0642
)0.0143
0.0255
)1.026
3.094
)1.110
1.757
0.0307
0.0433
0.0176
0.0137
0.728
1.420
0.856
0.755
0.0254
0.0075
0.0233
0.0017
0.591
0.246
1.122
0.104
F-Statistic
0.463
0.519
1.861
0.001
7.485
4.203
0.058
0.020
0.115
0.654
R2
0.7696
0.6249
0.6932
0.5583
0.5523
0.3123
0.4854
0.2634
0.5967
0.4274
0.5811
0.3483
0.6291
0.5358
0.5444
0.4632
0.6558
0.4809
0.5968
0.4698
A. Akhigbe, A.M. Whyte / Journal of Banking & Finance 25 (2001) 393±417
Portfolio
409
410
Portfolio
Medium-sized banks
Short-term
Long-term
Small banks
Short-term
Long-term
High credit risk banks
Short-term
Long-term
Moderate credit risk banks
Short-term
Long-term
Low credit risk banks
Short-term
Long-term
Time interval
(bmp )
t-Statistic
Pre
Post
Pre
Post
0.7667
0.6135
0.6243
0.6460
9.669
8.731
15.596
13.899
Pre
Post
Pre
Post
0.6549
0.4428
0.5999
0.6342
4.747
2.980
9.388
5.686
Pre
Post
Pre
Post
1.3260
0.8120
1.0138
0.7903
12.292
9.791
19.623
15.071
Pre
Post
Pre
Post
0.9868
0.7101
0.7925
0.8019
11.936
6.665
18.754
11.200
Pre
Post
Pre
Post
0.7350
0.5207
0.6117
0.5605
10.372
7.026
16.048
10.984
F-Statistic
2.091
0.126
1.095
0.071
14.268
9.220
4.209
0.013
4.368
0.646
(bip )
t-Statistic
)0.0276
0.0390
)0.0234
0.0240
)0.940
1.760
)1.611
1.720
0.0447
)0.0097
0.0411
0.0221
0.874
)0.207
1.777
0.661
0.0356
0.0326
0.0397
0.0244
0.890
1.248
2.122
1.552
)0.0118
0.0462
)0.0243
0.0195
)0.386
1.374
)1.587
0.908
)0.0077
)0.0116
)0.0014
0.0030
)0.295
)0.498
)0.101
0.196
F-Statistic
3.276
5.541
0.615
0.219
0.004
0.393
1.625
2.757
0.012
0.046
R2
0.5046
0.4548
0.4561
0.3987
0.1888
0.0839
0.2322
0.0997
0.6101
0.5045
0.5653
0.4368
0.6020
0.3276
0.5467
0.2989
0.5329
0.3374
0.4653
0.2981
A. Akhigbe, A.M. Whyte / Journal of Banking & Finance 25 (2001) 393±417
Table 5 (Continued)
Finance companies
Short-term
REITs
Short-term
Long-term
a
0.9788
1.2857
0.9067
1.1497
8.215
8.198
15.251
11.680
Pre
Post
Pre
Post
0.6109
0.4853
0.5068
0.4773
6.230
4.261
9.818
5.120
2.428
4.468
0.698
0.077
0.0246
0.0815
0.0184
0.0116
)0.0441
)0.0058
)0.0163
0.0012
0.558
1.649
0.853
0.393
)1.214
)0.161
)0.873
0.041
0.736
0.034
0.563
0.270
0.4115
0.4238
0.4392
0.3153
0.3082
0.1577
0.2486
0.0811
This table shows changes in risk for several portfolios. The change in risk in the short-term period is assessed by computing the bs over a 100 day preand post-event period while the long-term impact is assessed using a 300 day pre- and post-event period. F-statistics are calculated under the null
hypothesis that the bs in the pre- and post-FDICIA period are equal. The F-statistics are calculated as follows: ((residual sum of squares restricted
model±residual sum of squares unrestricted model/q))/((residual sum of squares unrestricted model/n ÿ k)), where q is the number of restrictions, n the
number of observations and k is the number of parameter estimates. Thus, the F-statistic has (1, 594) degrees of freedom in the long-term interval.
*
Signi®cant at the 10% level.
**
Signi®cant at the 5% level.
***
Signi®cant at the 1% level.
A. Akhigbe, A.M. Whyte / Journal of Banking & Finance 25 (2001) 393±417
Long-term
Pre
Post
Pre
Post
411
412
A. Akhigbe, A.M. Whyte / Journal of Banking & Finance 25 (2001) 393±417
Table 6
Estimates of shifts in unsystematic risk (Var(ept )) by bank capitalization, size and credit riska
Portfolio
Pre-FDICIA
Post-FDICIA
F-Statistic
All banks
Short-term
Long-term
0.000016
0.000012
0.000010
0.000011
1.60
1.12
Well capitalized banks
Short-term
Long-term
0.000026
0.000017
0.000021
0.000025
1.20
1.44
Moderately capitalized banks
Short-term
Long-term
0.000024
0.000016
0.000015
0.000018
1.64
1.16
Poorly capitalized banks
Short-term
Long-term
0.000063
0.000039
0.000031
0.000028
2.02
1.40
Large banks
Short-term
Long-term
0.000066
0.000040
0.000032
0.000024
2.07
1.68
Medium-sized banks
Short-term
Long-term
0.000031
0.000020
0.000017
0.000017
1.85
1.18
Small banks
Short-term
Long-term
0.000093
0.000050
0.000074
0.000095
1.26
1.91
High credit risk banks
Short-term
Long-term
0.000057
0.000033
0.000023
0.000021
2.46
1.55
Moderate credit risk banks
Short-term
Long-term
0.000033
0.000022
0.000038
0.000039
1.14
1.80
Low credit risk banks
Short-term
Long-term
0.000025
0.000018
0.000018
0.000020
1.33
1.12
Finance companies
Short-term
Long-term
0.000069
0.000043
REITs
Short-term
Long-term
0.000047
0.000032
0.000083
0.000074
0.000044
0.000066
1.19
1.72
1.08
2.04
a
The short-term impact of FDICIA on total risk is assessed by comp
www.elsevier.com/locate/econbase
The impact of FDICIA on bank returns and
risk: Evidence from the capital markets
Aigbe Akhigbe a, Ann Marie Whyte
b,*
a
b
Florida Atlantic University, Boca Raton FL, USA
Department of Finance, College of Business Administration, University of Central Florida,
P.O. Box 161400, Orlando, FL 32816-1400, USA
Received 12 March 1999; accepted 4 November 1999
Abstract
This study examines the impact of the Federal Deposit Insurance Corporation Improvement Act (FDICIA) of 1991 on bank stock returns and risk. We ®nd that FDICIA
had a generally positive eect on bank stock returns and resulted in a signi®cant reduction in bank risk. The extent of the risk reduction varies based on the capitalization,
size, and credit risk of the institutions with poorly capitalized, large, and high credit risk
banks experiencing the greatest risk reduction. The results obtained using two separate
control groups also bolster the conclusion that FDICIAÕs passage resulted in a significant decline in bank risk. Ó 2001 Elsevier Science B.V. All rights reserved.
JEL classi®cation: G21; G28
Keywords: Bank risk; Wealth eects; Bank regulation
1. Introduction
The passage of the Federal Deposit Insurance Corporation Improvement
Act (FDICIA) in 1991 marked a signi®cant regulatory milestone for the
*
Corresponding author. Tel.: +1-407-823-3945; fax: +407-823-6676.
E-mail addresses: [email protected] (A.M. Whyte).
0378-4266/01/$ - see front matter Ó 2001 Elsevier Science B.V. All rights reserved.
PII: S 0 3 7 8 - 4 2 6 6 ( 9 9 ) 0 0 1 3 1 - 4
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A. Akhigbe, A.M. Whyte / Journal of Banking & Finance 25 (2001) 393±417
banking industry. The act contains several important provisions including
improving the capitalization of the Federal Deposit Insurance Corporation
(FDIC), more stringent capital requirements, early regulatory intervention in
the aairs of troubled or undercapitalized banks, prompt failure resolution,
and risk-based deposit insurance premiums.
This study examines changes in capital market measures of risk for a sample
of bank holding companies (BHCs) and banks following the passage of
FDICIA. A secondary focus of the study is to re-examine the wealth eects
surrounding FDICIAÕs passage. Two previous studies by Madura and Bartunek (1995) and Liang et al. (1996) have examined the wealth eects of
FDICIA. This study complements their work using a larger sample of institutions and expands the analysis to include an examination of the impact of
FDICIA on risk.
Several studies have examined the eects of regulatory intervention on
shareholder wealth. Cornett and Tehranian (1989) examine the wealth eects of
the Depository Institutions Deregulation and Monetary Control Act
(DIDMCA) of 1980 and ®nd that shareholders of large commercial banks
experienced signi®cant positive abnormal returns while shareholders of small
commercial banks and savings and loans (S&Ls) experienced signi®cant negative returns. Cornett and Tehranian (1990) ®nd that the Garn-St. Germain
Depository Institutions Act of 1982 resulted in positive abnormal returns to
shareholders of large S&Ls and commercial banks and negative returns for
small S&Ls and banks. Sundaram et al. (1992) show that the passage of the
Financial Institutions Reform, Recovery, and Enforcement Act (FIRREA) of
1989 resulted in positive abnormal returns for both banks and S&Ls. Alexander
and Spivey (1994) examine the impact of the Competitive Equality Banking Act
(CEBA) of 1987 on the returns of S&Ls and document negative abnormal
returns for well capitalized S&Ls and positive eects for less capitalized S&Ls.
More recently, Madura and Bartunek (1995) and Liang et al. (1996) examine the wealth eects of FDICIA. Madura and Bartunek (1995) use a
sample of 89 institutions and ®nd that small and medium-sized banks were
favorably aected by events surrounding FDICIAÕs passage while large banks
were negatively aected by FDICIA's passage. They also ®nd that banks with
high capital to asset ratios experienced a more favorable share price response.
Liang et al. (1996) use a sample of 164 BHCs and ®nd that the shareholders of
well capitalized banks bene®ted from the enactment of FDICIA while those of
undercapitalized banks experienced signi®cant losses. This is consistent with
Madura and BartunekÕs (1995) ®nding that banks with high capital to asset
ratios reacted more favorably than banks with relatively low capital to asset
ratios. However, while Madura and Bartunek (1995) document a positive reaction for small and medium-sized banks, Liang et al. (1996) ®nd that the
reaction of large and small banks is insigni®cant and statistically indistinguishable. Both studies focus exclusively on the impact of FDICIA on returns,
A. Akhigbe, A.M. Whyte / Journal of Banking & Finance 25 (2001) 393±417
395
but do not consider the legislation's impact on bank risk. Since regulators are
concerned with the solvency of the banking system, they are concerned with
both wealth eects and risk changes associated with regulatory intervention.
This study ®lls a gap in the literature by examining changes in bank risk following FDICIA's passage.
Studies focusing on the impact of regulation on bank risk include Mingo
(1978), Koehn and Stangle (1980), Smirlock (1984), Allen and Wilhelm (1988),
Bundt et al. (1992) and Sundaram et al. (1992). Mingo (1978) ®nds that deposit-rate ceilings increase a bank's total risk while Koehn and Stangle (1980)
®nd that systematic risk is not aected by deposit rate ceilings. Smirlock (1984)
provides evidence that the deregulation of deposit rates resulting from the
passage of the DIDMCA of 1980 had no impact on systematic or unsystematic
risk. Similar ®ndings are documented by Allen and Wilhelm (1988). However,
Aharony et al. (1988) ®nd that DIDMCA's passage resulted in an increase in
total risk for both money center and regional banks but a decrease in total risk
for thrifts. More recently, Bundt et al. (1992) provide evidence that DIDMCA's passage resulted in increases in both systematic and unsystematic
measures of bank risk. Sundaram et al. (1992) show that the passage of the
FIRREA of 1989 increased the risk of both banks and S&Ls. Finally, Alexander and Spivey (1994) ®nd that less capitalized institutions experienced a
signi®cant decrease in risk following CEBAÕs passage.
Overall, these studies provide ample precedent for the proposition that
regulation can potentially impact both shareholder wealth and risk. Furthermore, they suggest that the impact is likely to be dependent on factors such as
bank size and capitalization. Accordingly, this study examines the impact of
FDICIA on shareholder wealth and bank risk. Previous studies by Madura and
Bartunek (1995) and Liang et al. (1996) have already demonstrated that
FDICIA's provisions resulted in signi®cant wealth eects for bank shareholders. We add to these studies by using a broader sample of institutions and
examining the impact on bank risk. FDICIA's passage may have contributed to
a change in bank risk since several key provisions of the legislation are aimed at
promoting stability and discouraging excessive risk taking in the banking industry. For example, the imposition of more stringent capital requirements
should reduce bank risk, particularly in the case of poorly capitalized banks.
Similarly, the introduction of risk-based insurance premiums imposes market
discipline and should reduce risk-taking behavior on the part of banks.
The seemingly unrelated regression (SUR) model is used to assess the wealth
eects of FDICIA. The risk shift analysis is conducted using several capital
market measures of risk; total, systematic, interest rate, and unsystematic risks.
The study utilizes a methodology similar to that employed by Smirlock (1984),
and Aharony et al. (1986, 1988). The methodology estimates several capital
market measures of risk over a pre- and post-FDICIA period for several equallyweighted portfolios of banks based on capitalization, size, and credit risk.
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A. Akhigbe, A.M. Whyte / Journal of Banking & Finance 25 (2001) 393±417
The empirical evidence is consistent with the proposition that the wealth
eects of FDICIA are generally positive. Furthermore, the evidence shows that
the institutions experienced a signi®cant reduction in total, systematic, and
unsystematic risk following FDICIAÕs passage, and the results vary based on
the capitalization, size, and credit risk of the institutions. In particular, we ®nd
that poorly capitalized, large, and high credit risk banks experience the greatest
reduction in risk. The results for two separate control groups provide further
support for the conclusion that the observed reduction in bank risk is attributable to FDICIAÕs passage and not to economy-wide forces. In contrast, there
is no evidence of a signi®cant change in interest rate risk in the wake of
FDICIAÕs passage. This result is not surprising since FDICIA does not explicitly address interest rate risk. Consequently, banks are not motivated to
alter their interest rate exposure in the wake of FDICIAÕs passage. Overall, the
®ndings support a signi®cant reduction in risk in the banking industry following the passage of FDICIA.
These ®ndings have important implications for regulators and shareholders.
Regarding regulators, it appears that FDICIAÕs provisions including riskbased capital requirements, risk-based insurance premiums, limited discount
window access, and prompt corrective action had the desired eect on bank
risk. Regarding stockholders, the results suggest that well diversi®ed shareholders should reduce their required rates of return on bank stocks in the wake
of FDICIAÕs passage.
The remainder of the paper is organized as follows. First, hypotheses related
to key provisions are developed and the possible implications for changes in
bank risk are presented. Next, the data and methodology are detailed and the
results are discussed. Finally, the conclusions are presented and the implications are oered.
2. Hypotheses related to key provisions of FDICIA
This section outlines key provisions of FDICIA and the possible implications for bank risk. 1 From an investment standpoint, stockholders who hold
well-diversi®ed portfolios are only concerned with the systematic risk of an
institution. Thus, if FDICIAÕs passage does not impact systematic risk,
stockholders should be indierent to this type of regulation. If, however,
1
Since the wealth eects already been examined in previous studies, this section focuses on
hypotheses related to the implications of FDICIA for bank risk in the interest of brevity. In
general, the emphasis of the law on promoting safety and soundness should be good news for the
banking industry as a whole and may result in positive wealth eects. It is possible, however, that
some provisions, including higher insurance premiums, may result in negative wealth eects.
A. Akhigbe, A.M. Whyte / Journal of Banking & Finance 25 (2001) 393±417
397
FDICIAÕs passage reduces systematic risk, stockholders should reduce their
required returns accordingly. From a regulatory standpoint, the total risk of an
institution is relevant, not just systematic risk (Mingo, 1978). Peltzman (1976)
argues that regulation alters the riskiness of the regulated ®rm by lowering the
variability of earnings which should reduce both systematic and unsystematic
risks. Accordingly, this study examines the impact of FDICIAÕs passage on
total, systematic, and unsystematic risks and, as such, provides implications for
both stockholders and regulators.
Several key provisions of FDICIA are likely to contribute to a signi®cant
change in bank risk. Based on the literature review and the evidence provided
by Madura and Bartunek (1995) and Liang et al. (1996) for the wealth eects of
FDICIA, the legislationÕs impact on risk may vary with bank capitalization
and size. Thus, the hypotheses are developed for each provision based on bank
capitalization and size. We also examine whether the risk changes vary based
on the credit risk of the institutions.
2.1. Improving the capitalization of the FDIC
FDICIA provided a temporary injection of an additional $30 billion into the
FDIC. Under FDICIA, permanent capitalization of the FDIC is provided by
the deposit insurance premiums paid by banks. This improved capitalization
may have conveyed a positive signal to the market and may have reduced the
marketÕs perception of risk since the FDIC is now better positioned to handle
losses in the event that a failure occurs. This argument suggests that all banks,
irrespective of capitalization, size, or credit risk, may experience an overall
reduction in risk.
2.2. Prompt corrective action
FDICIA re¯ects a shift in emphasis from regulatory forbearance to prompt
corrective action in the case of undercapitalized banks. With prompt corrective
action, banks face stringent regulatory measures and the threat of closure if they
become undercapitalized. Dahl and Spivey (1995) argue that prompt corrective
action should reduce losses in at least three ways. First, prompt corrective action may lower the resolution costs for undercapitalized banks which ultimately
fail by limiting the length of time a bank is undercapitalized prior to failure.
Second, prompt corrective action should discourage healthy banks from becoming undercapitalized. Third, prompt corrective action may reduce the
number of failures of undercapitalized banks, thereby reducing the resolution
costs borne by the FDIC. These arguments suggest that poorly capitalized
banks should experience a signi®cant reduction in risk as they are forced to
improve their capitalization. The impact may also vary based on bank size.
Madura and Bartunek (1995) argue that large banks tend to have lower capital
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A. Akhigbe, A.M. Whyte / Journal of Banking & Finance 25 (2001) 393±417
to asset ratios and to invest in riskier assets than small banks since they are more
diversi®ed. To the extent that FDICIA threatens early intervention, large,
poorly capitalized banks should have an incentive to decrease their risk-taking
activities. Similarly, banks with high credit risk and low capital to asset ratios
should also have an incentive to reduce risk to avoid the threat of early closure.
2.3. Discount window access
FDICIA limits the access of undercapitalized banks to the discount window,
eectively curtailing the ability of these institutions to boost short-term liquidity by borrowing from the discount window. This provision should serve
as an incentive for undercapitalized banks to quickly improve their capital
positions or face closure by regulatory authorities. The same incentive should
exist regardless of size since both large and small banks would have limited
access to the discount window if they become signi®cantly undercapitalized.
High credit risk banks would also have an incentive to reduce risk since they
can no longer rely on the discount window to provide temporary liquidity.
2.4. Too-big-to-fail doctrine
FDICIA eectively eliminates the too-big-to-fail doctrine (Wall, 1993). The
act prohibits the FDIC from protecting deposits above the maximum insurance
limit, and provides that exceptions can only be made by agreement of the
FDIC, the Federal Reserve, and the Treasury. This provision may increase the
perceived riskiness of large banks since the FDIC will only provide limited
coverage in the event of failure. On the other hand, large banks now have an
incentive to reduce risk since they can no longer rely on the FDIC to rescue
them or to protect uninsured depositors. Thus, de jure uninsured depositors
who are aware of this change now have an incentive to monitor the activities of
banks thereby limiting the risk-taking activities of banks. Large banks may,
therefore, experience a reduction in risk following FDICIAÕs passage.
2.5. Risk-based deposit insurance premiums
FDICIA mandates risk-based deposit insurance premiums, with undercapitalized banks being forced to pay higher insurance premiums than well capitalized banks. This provision reduces the moral hazard problem and should
encourage banks to reduce excessive risk-taking since they will ultimately be
penalized with higher insurance premiums. Based on this provision, high risk
banks (poorly capitalized and or high credit risk banks) should experience a
signi®cant reduction in risk.
Overall, FDICIAÕs provisions suggest that banks should experience a signi®cant change in risk following the lawÕs passage. In particular, banks should
A. Akhigbe, A.M. Whyte / Journal of Banking & Finance 25 (2001) 393±417
399
experience a reduction in risk in the post-FDICIA era relative to the preFDICIA era.
3. Data and methodology
The eects of FDICIA on shareholder wealth and bank risk are examined
using daily common stock returns for BHCs and banks over the period surrounding FDICIAÕs passage. The sample is constructed by identifying all institutions on the Center for Research in Security Prices (CRSP) tapes with 602,
603 or 671 as the standard industry classi®cation (SIC) code, and which have
returns for 300 trading days in the pre- and post-event periods. After generating this list, the MoodyÕs Bank and Finance Manual for 1991 is used to verify
that the listed institutions are indeed BHCs or banks. This procedure resulted
in a ®nal sample of 322 BHCs and banks.
As with most regulations, the legislative process surrounding FDICIAÕs
passage was complex and involved the announcement of various events leading
up to the ®nal passage of the law. Table 1 identi®es the date of each event and
provides a brief description. The event dates and descriptions are obtained
from Table 1 of the Liang et al. (1996) study and are presented here to provide
clarity in interpreting the results.
The SUR model is used to estimate the share price response of the bank
portfolios. Johnston (1984) argues that in the presence of contemporaneous
correlation the SUR methodology generates more ecient estimates. The
model is estimated as
Rpt ap bmp Rmt bip Rit
9
X
cpk Dk ept ;
1
k1
where Rpt is the return on the bank portfolio on day t, ap the intercept term, bmp
measures market/systematic risk of the portfolio, Rmt the return on the CRSP
equally-weighted market portfolio on day t, bip measures interest rate risk of
the portfolio, Rit the daily change in the interest rate on the 30 year Treasury
bond, 2 cpk measures the sensitivity of the portfolio to event k, Dk a dummy
variable equal to 1 for the kth event date and 0 otherwise, ept is the disturbance
term on the portfolio on day t.
Eq. (1) is estimated using daily returns for all trading days in 1991. The
model is estimated for all banks and several additional bank portfolios based
2
Kane and Unal (1988) note that bank and S&L stock returns are not responsive to short rates
but long rates have a signi®cant eect (Unal and Kane, 1987). Thus, following their methodology,
this paper uses the returns on long-term government bonds to proxy the unanticipated changes in
the interest rate index.
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A. Akhigbe, A.M. Whyte / Journal of Banking & Finance 25 (2001) 393±417
Table 1
Events surrounding the passage of FDICIAa
Event
Date
Event description
D1
1/2/91
D2
6/5/91
D3
8/5/91
D4
1/7/91
D5
5/11/91
D6
7/11/91
D7
22/11/91
D8
27/11/91
D9
20/12/91
FDIC chairman says the Bank Insurance Fund needs cash infusion of up
to $10 billion
The Federal Reserve Bank opposes an important provision in the bill
that could restrict its ability to provide liquidity to troubled banks
The House Financial Institutions Subcommittee approves a bill requiring
regulators to intervene quickly in the aairs of weak banks. The bill also
improves the insurance fund and imposes new auditing standards on
banks
House Banking Committee votes to accept most of the Bush AdministrationÕs proposals to restructure banking laws
House defeats banking bill but the House Banking Committee is
expected to rewrite the bill
House Banking Committee passes a scaled down version of the banking
bill
House and Senate pass separate bills which provide a $70 billion line of
credit to the FDIC and impose new regulations aimed at reducing bank
failures
House accepts Senate provision requiring banks to repay (through higher
insurance premiums) a $30 billion line of credit over a 15 year period
President signs FDICIA into law
a
This table shows the nine event dates and a brief description of each event surrounding FDICIA's
passage. The event dates and descriptions are obtained from the study by Liang et al. (1996).
on capitalization (well capitalized, moderately capitalized, and poorly capitalized banks), size (large, medium-sized, and small banks), and credit risk
(high, moderate, and low credit risk banks). The data on capitalization, size,
and credit risk are obtained from the Bank Condition and Income database on
the Federal Reserve Bank of ChicagoÕs web site. The data from the Bank
Condition and Income reports are matched to the original sample of 322 banks
using the Moody's Bank and Finance Manual for 1991.
The impact of FDICIA on risk is estimated using the methodology outlined
by Aharony et al. (1986, 1988) and Smirlock (1984). The risk measures are
estimated over a short-term interval and a long-term interval. The short-term
interval includes 100 trading days prior to the event period and 100 trading
days after the event period. The long-term interval includes 300 trading days
prior to the event period and 300 trading days after the event period. Recognizing that the numerous announcements leading up to FDICIAÕs passage may
alter the marketÕs expectations, we de®ne the pre-event period as the interval
preceding the ®rst announcement (D1 ) on 1 February 1991 that the chairman
of the FDIC stated that the Bank Insurance Fund (BIF) needed a signi®cant
cash infusion. Similarly, the post-event period is de®ned as the interval following the last news announcement that the bill had been signed into law on
A. Akhigbe, A.M. Whyte / Journal of Banking & Finance 25 (2001) 393±417
401
December 20, 1991 (D9 ). The capital market measures of risk are obtained
using the two-index model which has been utilized extensively in the banking
literature: 3
Rpt ap bmp Rmt bip Rit ept ;
2
where the parameters are as previously de®ned in Eq. (1).
One potential problem in using the two-index model is the need to specify
the relationship between the interest rate change and the market return. Some
studies have dealt with this problem using orthogonalization (Chance and
Lane, 1980; Flannery and James, 1984b). However, as noted by Giliberto
(1985) and Kane and Unal (1988) the orthogonalization procedures produce
biased t-tests. Thus, following Kane and Unal (1988) this study uses the unorthogonalized two-index model. 4 Based on Eq. (2) the variance of the return
on the portfolio is given by
Var Rp b2mp Var Rm b2ip Var Ri Var ep ;
3
where Var is the variance operator. The terms Var Rm and Var Ri re¯ect
market wide factors, whereas b2mp , b2ip , and Var ep are aected by portfolio
speci®c characteristics. Thus, changes in the variance of bank returns Var Rp
could be due to changes in market risk b2mp Var Rm , interest rate risk
b2ip Var Ri , or unsystematic risk Var ep . 5
3
See, for example (Flannery and James, 1984a,b; Aharony et al., 1986, 1988).
To provide further justi®cation for using the unorthogonalized two-index model, Eq. (1) is reestimated as follows. First, the following equation is estimated: Rit apt bim Rmt ept . Then, the
residuals from the equation are substituted into Eq. (1) for the interest rate index (Chance and
Lane, 1980; Aharony et al., 1986). The results using the orthogonalized model are qualitatively
similar to those obtained using the unorthogonalized model. Hence, the results for the
unorthogonalized model are reported. The complete results are available from the authors.
5
Eq. (3) implicitly assumes independence between the interest rate series Rit and the market
return Rmt . To determine whether a covariance term needs to be included in the equation, Eq. (3)
is re-estimated as
4
Var Rp b2mp Var Rm b2ip Var Ri 2bmp bip Cov Rm Ri Var ep :
In all instances, inclusion of the covariance term did not materially alter the variance estimates. For
example, in the pre-FDICIA short-term period for the portfolio of all banks, the covariance term is
calculated as: 2 1:0109 0:0042 ÿ0:000019 0:0000002. Addition of this result to the original
variance estimate of 0.000068 results in no signi®cant change. Further con®rmation of this result is
obtained by using the orthogonalized model described in Footnote 4. The variance estimates are
then obtained using the orthogonalized model and the results are qualitatively similar to the estimates based on Eq. (3). Thus, the variance estimates reported in the paper are based on estimating
Eq. (3). All results are available from the authors.
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A. Akhigbe, A.M. Whyte / Journal of Banking & Finance 25 (2001) 393±417
The following hypotheses (H) are tested for the sample of all banks:
H1
H2
H3
H4
There is no signi®cant dierence in total risk in the pre-and postFDICIA era for the equally-weighted portfolio of all banks.
There is no signi®cant dierence in systematic risk in the pre-and
post-FDICIA era for the equally-weighted portfolio of all banks.
There is no signi®cant dierence in interest rate risk in the pre-and
post-FDICIA era for the equally-weighted portfolio of all banks.
There is no signi®cant dierence in unsystematic risk in the pre-and
post-FDICIA era for the equally-weighted portfolio of all banks.
The hypotheses are also tested for several subsamples based on capitalization,
size, and credit risk. 6
The analysis is also conducted for two separate control groups. The analysis
of control groups is necessary because during the period surrounding FDICIAÕs passage, a number of events occurred that may have had an impact on
bank risk. First, Berger (1995) argues that banks were generally riskier in the
1980s but raised capital above optimal levels in the early 1990s because of
regulatory changes and unexpectedly high earnings. Second, the Federal Reserve had taken steps to counteract the economic recession and improve bank
capitalization such as reducing the reserve requirements in 1990 (Cosimano
and McDonald, 1998). Finally, the overall economic recovery may have contributed to a decrease in bank risk independent of FDICIA.
To test whether the changes in risk documented for the sample of banks are
most likely attributable to FDICIA and not to these other factors, the above
analysis is repeated for two dierent control samples; ®nance companies and real
estate investment trusts (REITs). Finance companies are in the same line of
business as banks on the asset side of their balance sheet, but are not subject to the
provisions of FDICIA since they do not hold deposits. Similarly, REITs would
be subject to the same real estate problems as banks but would not be subject to
the provisions of FDICIA. Thus, both ®nance companies and REITs represent
the best pool of ®rms for constructing control samples. The sample of ®nance
companies and REITs is obtained from the list provided in volume two of the
Moody's Bank and Finance Manual for 1991. The list is then used to identify those
®nance companies and REITs which are publicly traded and for which return
data are available on CRSP over the sample period. This procedure resulted in a
®nal sample of 93 ®nance companies and 85 REITs. Since the provisions of
FDICIA do not apply to these ®rms, they should not experience a signi®cant
6
The analysis was also conducted for three portfolios formed on the basis of the interest rate risk
of the individual banks prior to FDICIA (high, moderate, and low interest rate risk). The results
were relatively uniform across the three groups. Thus, the risk reduction following FDICIA did not
vary much based on the interest rate risk of the institutions. The complete results are available from
the authors.
A. Akhigbe, A.M. Whyte / Journal of Banking & Finance 25 (2001) 393±417
403
reduction in risk following FDICIAÕs passage. Thus, the results of the control
samples will enable us to determine whether the observed changes in bank risk
are most likely attributable to FDICIAÕs passage.
4. Results
Table 2 provides a summary of the sample characteristics based on data
obtained from the Bank Condition and Income database. The table shows the
sample size and the mean and median capital to asset ratio, total assets, and
nonperforming loans to total assets for the sample banks over the three year
period prior to FDICIAÕs passage. The sample is partitioned into thirds for
each variable; upper third, middle third, and lower third. The full sample
consists of 322 institutions and the upper, middle, and lower thirds have 108,
107 and 107 institutions, respectively. The mean (median) capital to asset ratio
is 7.86 (7.28)% for all banks, 10.45 (9.42)% for the upper third (well capitalized
Table 2
Sample characteristics for all banks and portfolios based on capitalization, size, and credit riska
All banks
Well capitalized banks
Moderately capitalized banks
Poorly capitalized banks
All banks
Large banks
Medium-sized banks
Small banks
All banks
High credit risk banks
Moderate credit risk banks
Low credit risk banks
Mean capital to
asset ratio (%)
Median capital to
asset ratio (%)
Sample size
7.86
10.45
7.26
5.90
7.28
9.42
7.29
6.00
322
108
107
107
Mean total
assets (in billions
of dollars)
Median total assets
(in billions of
dollars)
Sample size
5.40
14.92
1.01
0.26
0.82
6.56
0.82
0.25
322
108
107
107
Mean nonperforming loans/
total assets (%)
Median nonperforming loans/total
assets (%)
Sample size
1.08
5.13
1.08
0.24
322
108
107
107
3.65
9.60
1.09
0.25
a
This table shows the mean and median capital to asset ratio, total assets, and credit risk (measured
as the ratio of nonperforming loans to total assets) for the sample of institutions over the three year
period prior to FDICIAÕs passage. The sample is partitioned into the upper, middle, and lower
third for each variable. The sample includes all banks for which return data are available on CRSP
for the full sample period and for which data are available on the FDICÕs Bank Income and
Condition Reports for the three years prior to FDICIA.
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A. Akhigbe, A.M. Whyte / Journal of Banking & Finance 25 (2001) 393±417
banks), 7.26 (7.29)% for the middle third (moderately capitalized banks) and
5.90 (6.0)% for the lower third (poorly capitalized banks). The mean total
assets for the sample of 322 banks is $5.4 billion while the median is $0.82
billion. The upper third (large banks) has mean (median) total assets of $14.92
billion ($6.56 billion), the middle third (medium-sized banks) has $1.01 billion
(0.82 billion) while the lower third (small banks) has total assets of $0.26 billion
($0.25 billion). Finally, the mean (median) ratio of nonperforming loans to
total assets for all banks is 3.65 (1.08)%, 9.60 (5.13) for the upper third (high
credit risk banks), 1.09 (1.08) for the middle third (moderate credit risk banks)
and 0.25 (0.24) for the lower third (low credit risk banks).
Table 3 shows the share price response of the bank portfolios to the events
surrounding FDICIAÕs passage. The portfolio of all banks reacted positively
(return of 0.8%) to the news that the chairman of the FDIC stated that the BIF
needed an infusion of up to $10 billion (D1 ). The same positive pattern is observed for the portfolios of poorly capitalized, moderately capitalized, and medium-sized banks although the portfolio of poorly capitalized banks is only
marginally signi®cant at the 10% level. Overall, the portfolios do not experience a
signi®cant reaction to the events D2 through D8 . The ®nal event D9 , results in a
positive reaction for the portfolio of all banks (return of 0.9%) and the portfolio
of poorly capitalized banks (return of 1.7%). The portfolio of large banks also
experienced a return of 1.3% which is statistically signi®cant at the 10%. Overall,
the results suggest that the news that the BIF would receive an infusion of up to
$10 billion was good news for banks as was the ultimate passage of FDICIA (D9 ).
This suggests that the provisions of FDICIA aimed at improving the safety and
soundness of the banking system had a positive impact on bank stocks.
Our results contrast with those documented by Liang et al. (1996). They report that banks reacted adversely to D1 . In contrast, we ®nd that most portfolios
reacted favorably to D1 . They document a positive reaction to D4 (the news that
the House Banking Committee voted to accept most of the provisions of FDICIA) while we ®nd no signi®cant reaction to that event. They argue that this
positive reaction suggests that some provisions of FDICIA were good news, on
average, for the banking industry. Finally, we document a positive reaction to
D9 while they ®nd no signi®cant reaction. Overall, we document a positive reaction to FDICIA while they document both positive and negative wealth effects. The dierence in results may arise because we use a comprehensive sample
of 322 BHCs and banks while they use a sample of 164 BHCs. 7 Our results are
7
We include the interest rate index in Eq. (1) while Liang et al. (1996) do not. To ensure that the
dierences in results are not driven by the use of a slightly dierent model, we re-estimate our
results using the model utilized in their study. Overall, the results are qualitatively similar to those
obtained using the two-index model. Thus, the results using the two-index model are reported to be
consistent with the risk shift methodology.
405
A. Akhigbe, A.M. Whyte / Journal of Banking & Finance 25 (2001) 393±417
Table 3
Wealth eects of FDICIA
Rpt ap bmp Rmt bip Rit
9
X
cpk Dk ept
1
k1
Bank portfolios
Market
model
parameters
All
banks
Well
capitalized
banks
Moderately
capitalized
banks
Poorly
capitalized
banks
Large
banks
Medium-sized
banks
Small
banks
ap
0.002
(1.508)
0.869
(28.941)
)0.023
()1.842)
0.008
(2.027)
0.001
(0.090)
)0.002
()0.427)
)0.003
()0.659)
)0.002
()0.560)
)0.001
()0.145)
0.002
(0.373)
0.002
(0.468)
0.009
(2.197)
0.697
0.688
0.003
(1.938)
0.681
(17.767)
)0.035
()2.222)
0.002
(0.399)
)0.006
()1.239)
0.001
(0.209)
)0.004
()0.790)
)0.001
()0.074)
)0.002
()0.406)
0.006
(1.185)
0.002
(0.445)
0.002
(0.448)
0.468
0.453
0.002
(1.759)
0.75
(21.513)
)0.026
()1.797)
0.009
(2.075)
0.009
(1.949)
)0.001
()0.083)
)0.002
()0.468)
)0.004
()0.803)
)0.004
()0.773)
)0.001
()0.078)
)0.004
()0.954)
0.007
(1.470)
0.566
0.553
0.001
)0.03
1.176
(21.439)
)0.008
()0.354)
0.012
(1.733)
)0.001
()0.164)
)0.006
()0.794)
)0.002
()0.219)
)0.003
()0.359)
0.004
(0.537)
)0.001
()0.159)
0.007
)1.036
0.017
(2.333)
0.559
0.546
0.001
)0.722
1.301
(25.026)
)0.027
()1.247)
0.009
)1.288
)0.001
()0.178)
)0.004
()0.567)
0.001
(0.092)
)0.001
()0.022)
)0.004
()0.585)
)0.005
()0.671)
)0.003
()0.471)
0.013
(1.883)
0.631
0.62
0.002
)1.612
0.674
(16.667)
)0.0271
()1.626)
0.015
(2.833)
)0.002
()0.299)
)0.001
()0.249)
)0.008
()1.501)
0.001
(0.099)
0.003
(0.601)
0.001
(0.115)
0.002
(0.436)
0.006
(1.095)
0.447
0.431
0.001
)0.71
0.61
(12.583)
)0.015
()0.740)
)0.001
()0.084)
0.004
(0.643)
0.001
(0.049)
)0.001
()0.038)
)0.007
()1.167)
)0.001
()0.118)
0.009
(1.401)
0.007
(1.059)
0.007
(1.107)
0.305
0.285
81.343
31.076
46.038
44.792
60.414
28.541
15.489
bmp
bip
D1
D2
D3
D4
D5
D6
D7
D8
D9
R2
Adjusted
R2
F-Value
Number of
banks
*
322
108
Signi®cant at the 10% level.
Signi®cant at the 5% level.
***
Signi®cant at the 1% level.
**
107
107
108
107
107
406
A. Akhigbe, A.M. Whyte / Journal of Banking & Finance 25 (2001) 393±417
consistent with Madura and Bartunek's (1995) ®nding that medium-sized banks
reacted favorably to the announcement of the bank reform proposal but are
inconsistent with their ®nding that large banks reacted negatively. It should be
noted, however, that Madura and Bartunek (1995) use a sample of 89 banks and
use slightly dierent event dates than those in this study and in Liang et al.
(1996). 8
The major contribution of this study is the examination of the impact of
FDICIA on bank risk. The results of this analysis are presented in Tables 4±7.
Table 4 shows the change in the variance of the portfolio returns surrounding
FDICIAÕs passage. The signi®cance of the changes in total risk is tested using
an F-statistic under the null H that the variance of returns is equal in the preand post-FDICIA periods. The portfolio of all banks experienced a signi®cant
reduction in total risk in both the short- and long-term intervals. Over the
short-term interval the variance declines by approximately 62% (from 0.000068
to 0.000026) and over the long-term interval by 37% (from 0.000038 to
0.000024). In both instances the reduction is signi®cant at the 1% level. While
most of the other bank portfolios experience a signi®cant decline in risk, the
reduction is most dramatic for the portfolios of poorly capitalized, large, and
high credit risk banks. Poorly capitalized banks experience a decline of 60%
(0.000171±0.000068) and 40% (0.000086±0.000052) in the short- and long-term
intervals, respectively, compared to a decline of 47% (0.000058±0.000031) and
0% (0.000033±0.000033) in the same intervals for well capitalized banks.
Similarly, large banks experience a decline of 68% (0.000191±0.000061) and
55% (0.000099±0.000045) for the short- and long-term intervals, respectively,
while small banks experience a decline of 30% (0.000115±0.000081) and an
increase of 62% (0.000065±0.000105) in the same intervals. Finally, high credit
risk banks experience a decline of 68% (0.000146±0.000047) and 51%
(0.000075±0.000037) in the short- and long-term intervals, respectively, while
low credit risk banks experience declines of 47% (0.000053±0.000028) and 15%
(0.000033±0.000028) in the same intervals. It is interesting to note that the
variance of the market portfolio also declines during the same period. Over the
short-term interval, the variance of the market portfolio declines from 0.000051
to 0.000035 (a decline of 31%) and from 0.000041 to 0.000026 (a decline of
37%) over the long-term interval. Thus, the decline in total risk is partly related
to the decline in the variance of market index over the same period. It is also
8
It should also be noted that it is dicult to compare the results for the portfolios across studies
because of diering de®nitions based on size and capitalization. For example Liang et al. (1996)
de®ne large banks as banks having at least $300 million in total assets while small banks have less
than $300 million in assets. This resulted in a sample of 152 large BHCs and only 12 small BHCs in
their study. Madura and Bartunek (1995) use the following de®nitions: large banks (total assets
greater than $15 billion), medium-sized banks (total assets between $2 and 15 billion) and small
banks (less than $2 billion).
A. Akhigbe, A.M. Whyte / Journal of Banking & Finance 25 (2001) 393±417
407
Table 4
Estimates of shifts in the variance of portfolio returns (Var Rp ) by bank capitalization, size, and
credit risk and estimates of shifts in (Var Rm ) and (Var Ri )a
Portfolio
Pre-FDICIA
Post-FDICIA
F-statistic
All banks
Short-term
Long-term
0.000068
0.000038
0.000026
0.000024
2.61
1.61
Well capitalized banks
Short-term
Long-term
0.000058
0.000033
0.000031
0.000033
1.85
1.01
Moderately capitalized banks
Short-term
Long-term
0.000059
0.000037
0.000025
0.000028
2.32
1.34
Poorly capitalized banks
Short-term
Long-term
0.000171
0.000086
0.000068
0.000052
2.52
1.66
Large banks
Short-term
Long-term
0.000191
0.000099
0.000061
0.000045
3.13
2.21
Medium-sized banks
Short-term
Long-term
0.000062
0.000036
0.000030
0.000027
2.04
1.31
Small banks
Short-term
Long-term
0.000115
0.000065
0.000081
0.000105
1.42
1.63
High credit risk banks
Short-term
Long-term
0.000146
0.000075
0.000047
0.000037
3.13
2.01
Moderate credit risk banks
Short-term
Long-term
0.000084
0.000048
0.000057
0.000056
1.48
1.16
Low credit risk banks
Short-term
Long-term
0.000053
0.000033
0.000028
0.000028
1.89
1.18
Finance companies
Short-term
Long-term
0.000118
0.000077
0.000143
0.000108
1.22
1.41
REITs
Short-term
Long-term
0.000068
0.000043
0.000052
0.000072
1.31
1.67
Market portfolio
Short-term
Long-term
0.000051
0.000041
0.000035
0.000026
1.48
1.60
408
A. Akhigbe, A.M. Whyte / Journal of Banking & Finance 25 (2001) 393±417
Table 4 (Continued)
Portfolio
Pre-FDICIA
Post-FDICIA
F-statistic
Interest rate index
Short-term
Long-term
0.000374
0.000313
0.000349
0.000286
1.07
1.09
a
The short-term impact of FDICIA on total risk is assessed by computing the portfolio variance
over a 100 day pre- and post-event short-term period while the long-term impact is assessed using a
300 day pre- and post-event period. The F-statistics for the variances are based on (99,99) degrees
of freedom in the numerator and denominator, respectively, for the short-term period and
(299,299) degrees of freedom for the long-term analysis. F-statistics are calculated under the null
hypothesis that the variances in the pre- and post-FDICIA period are equal and are calculated as
Var(Group A)/Var(Group B). In all cases Group A refers to the group with the larger variance and
Group B refers to the group with the smaller variance.
*
Signi®cant at the 10% level.
**
Signi®cant at the 5% level.
***
Signi®cant at the 1% level.
interesting to note that the variance of the interest rate index does not change
signi®cantly during the same period.
The results for the control group of ®nance companies show an increase in
the variance of the portfolio returns in the short-term but the change is
insigni®cant. Over the long-term interval, however, the variance actually increases by 40% (from 0.000077 to 0.000108) and the increase is statistically
signi®cant at the 1% level. Similar results are documented for the control
sample of REITs. Although the variance decreases in the short-term the decline
is statistically insigni®cant. Over the long-term interval, however, the variance
increases and the increase is signi®cant at the 1% level. This result is the opposite of that which is observed for the bank portfolios and provides preliminary evidence that the decline in bank risk is most likely attributable to
FDICIAÕs passage.
To identify the change in systematic risk following FDICIAÕs passage, the
change in the market beta and the interest rate beta are also examined. These
risk measures are particularly important to stockholders who hold well-diversi®ed portfolios. The F-statistic is used to test the signi®cance of the changes
under the null H that the coecients are equal in both periods. The results are
shown in Table 5. The market beta for all banks declines from 1.0109 to 0.6787
(a decline of 33%) over the short-term period and from 0.8035 to 0.7161 (a
decline of 11%) in the long-term period. In both instances, the decline is statistically signi®cant. The portfolios based on capitalization show a reduction in
risk in either the short- or long-term interval or both. However, the portfolios
based on size show greater variation in the results. While large banks experience a signi®cant reduction in risk in the short-term, small and medium-sized
banks experience no signi®cant change in risk. The portfolios based on credit
risk also provide some interesting insights. High credit risk banks experience
the most dramatic and consistent decline in systematic risk in both short- and
Table 5
Regression estimates of market (bmp ) and interest rate risk (bip ): pre- and post-event results by bank capitalization, size, and credit riska
All banks
Short-term
Long-term
Well-capitalized banks
Short-term
Long-term
Moderately capitalized banks
Short-term
Long-term
Poorly capitalized banks
Short-term
Long-term
Large banks
Short-term
Long-term
Time interval
(bmp )
t-Statistic
Pre
Post
Pre
Post
1.0109
0.6787
0.8035
0.7161
17.854
12.568
25.887
19.302
Pre
Post
Pre
Post
0.7922
0.5235
0.6264
0.5831
10.898
6.551
16.735
10.281
Pre
Post
Pre
Post
0.8144
0.5113
0.7195
0.6033
11.676
7.776
20.185
12.446
Pre
Post
Pre
Post
1.4549
1.0067
1.0700
0.9670
12.783
10.409
18.839
15.977
Pre
Post
Pre
Post
1.5678
0.9180
1.2013
0.9058
13.532
9.455
20.968
16.217
F-Statistic
18.032
3.267
6.189
0.405
9.999
3.732
9.007
1.541
18.475
0.654
(bip )
t-Statistic
0.0042
0.0226
0.0040
0.0154
0.202
1.329
0.353
1.381
0.0158
)0.0345
0.0086
0.0089
0.586
)1.371
0.634
0.524
)0.0265
0.0642
)0.0143
0.0255
)1.026
3.094
)1.110
1.757
0.0307
0.0433
0.0176
0.0137
0.728
1.420
0.856
0.755
0.0254
0.0075
0.0233
0.0017
0.591
0.246
1.122
0.104
F-Statistic
0.463
0.519
1.861
0.001
7.485
4.203
0.058
0.020
0.115
0.654
R2
0.7696
0.6249
0.6932
0.5583
0.5523
0.3123
0.4854
0.2634
0.5967
0.4274
0.5811
0.3483
0.6291
0.5358
0.5444
0.4632
0.6558
0.4809
0.5968
0.4698
A. Akhigbe, A.M. Whyte / Journal of Banking & Finance 25 (2001) 393±417
Portfolio
409
410
Portfolio
Medium-sized banks
Short-term
Long-term
Small banks
Short-term
Long-term
High credit risk banks
Short-term
Long-term
Moderate credit risk banks
Short-term
Long-term
Low credit risk banks
Short-term
Long-term
Time interval
(bmp )
t-Statistic
Pre
Post
Pre
Post
0.7667
0.6135
0.6243
0.6460
9.669
8.731
15.596
13.899
Pre
Post
Pre
Post
0.6549
0.4428
0.5999
0.6342
4.747
2.980
9.388
5.686
Pre
Post
Pre
Post
1.3260
0.8120
1.0138
0.7903
12.292
9.791
19.623
15.071
Pre
Post
Pre
Post
0.9868
0.7101
0.7925
0.8019
11.936
6.665
18.754
11.200
Pre
Post
Pre
Post
0.7350
0.5207
0.6117
0.5605
10.372
7.026
16.048
10.984
F-Statistic
2.091
0.126
1.095
0.071
14.268
9.220
4.209
0.013
4.368
0.646
(bip )
t-Statistic
)0.0276
0.0390
)0.0234
0.0240
)0.940
1.760
)1.611
1.720
0.0447
)0.0097
0.0411
0.0221
0.874
)0.207
1.777
0.661
0.0356
0.0326
0.0397
0.0244
0.890
1.248
2.122
1.552
)0.0118
0.0462
)0.0243
0.0195
)0.386
1.374
)1.587
0.908
)0.0077
)0.0116
)0.0014
0.0030
)0.295
)0.498
)0.101
0.196
F-Statistic
3.276
5.541
0.615
0.219
0.004
0.393
1.625
2.757
0.012
0.046
R2
0.5046
0.4548
0.4561
0.3987
0.1888
0.0839
0.2322
0.0997
0.6101
0.5045
0.5653
0.4368
0.6020
0.3276
0.5467
0.2989
0.5329
0.3374
0.4653
0.2981
A. Akhigbe, A.M. Whyte / Journal of Banking & Finance 25 (2001) 393±417
Table 5 (Continued)
Finance companies
Short-term
REITs
Short-term
Long-term
a
0.9788
1.2857
0.9067
1.1497
8.215
8.198
15.251
11.680
Pre
Post
Pre
Post
0.6109
0.4853
0.5068
0.4773
6.230
4.261
9.818
5.120
2.428
4.468
0.698
0.077
0.0246
0.0815
0.0184
0.0116
)0.0441
)0.0058
)0.0163
0.0012
0.558
1.649
0.853
0.393
)1.214
)0.161
)0.873
0.041
0.736
0.034
0.563
0.270
0.4115
0.4238
0.4392
0.3153
0.3082
0.1577
0.2486
0.0811
This table shows changes in risk for several portfolios. The change in risk in the short-term period is assessed by computing the bs over a 100 day preand post-event period while the long-term impact is assessed using a 300 day pre- and post-event period. F-statistics are calculated under the null
hypothesis that the bs in the pre- and post-FDICIA period are equal. The F-statistics are calculated as follows: ((residual sum of squares restricted
model±residual sum of squares unrestricted model/q))/((residual sum of squares unrestricted model/n ÿ k)), where q is the number of restrictions, n the
number of observations and k is the number of parameter estimates. Thus, the F-statistic has (1, 594) degrees of freedom in the long-term interval.
*
Signi®cant at the 10% level.
**
Signi®cant at the 5% level.
***
Signi®cant at the 1% level.
A. Akhigbe, A.M. Whyte / Journal of Banking & Finance 25 (2001) 393±417
Long-term
Pre
Post
Pre
Post
411
412
A. Akhigbe, A.M. Whyte / Journal of Banking & Finance 25 (2001) 393±417
Table 6
Estimates of shifts in unsystematic risk (Var(ept )) by bank capitalization, size and credit riska
Portfolio
Pre-FDICIA
Post-FDICIA
F-Statistic
All banks
Short-term
Long-term
0.000016
0.000012
0.000010
0.000011
1.60
1.12
Well capitalized banks
Short-term
Long-term
0.000026
0.000017
0.000021
0.000025
1.20
1.44
Moderately capitalized banks
Short-term
Long-term
0.000024
0.000016
0.000015
0.000018
1.64
1.16
Poorly capitalized banks
Short-term
Long-term
0.000063
0.000039
0.000031
0.000028
2.02
1.40
Large banks
Short-term
Long-term
0.000066
0.000040
0.000032
0.000024
2.07
1.68
Medium-sized banks
Short-term
Long-term
0.000031
0.000020
0.000017
0.000017
1.85
1.18
Small banks
Short-term
Long-term
0.000093
0.000050
0.000074
0.000095
1.26
1.91
High credit risk banks
Short-term
Long-term
0.000057
0.000033
0.000023
0.000021
2.46
1.55
Moderate credit risk banks
Short-term
Long-term
0.000033
0.000022
0.000038
0.000039
1.14
1.80
Low credit risk banks
Short-term
Long-term
0.000025
0.000018
0.000018
0.000020
1.33
1.12
Finance companies
Short-term
Long-term
0.000069
0.000043
REITs
Short-term
Long-term
0.000047
0.000032
0.000083
0.000074
0.000044
0.000066
1.19
1.72
1.08
2.04
a
The short-term impact of FDICIA on total risk is assessed by comp