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ISSUES IN F IN A N C IA L REG ULATIO N
W orking Paper Series
T h e Im p a c t o f D e p o s it In su ra n ce o n S & L
S h a r e h o l d e r s ’ R is k / R e t u r n T r a d e - o f f s
Elijah Brewer III
FEDERAL RESERVE B A N K
OF CHICAGO
WP- 1989/24
T h e
Im p a c t
o f D e p o s it In s u r a n c e
S h a r e h o ld e r s ' R is k / R e tu r n
o n
S & L
T r a d e -o ffs
This paper tests the hypothesis that deposit insurance has distorted risk/retum
trade-offs for financially distressed savings and loan associations (S&Ls).
When deposit insurance is underpriced, increases in the riskiness of the asset
portfolio and growth in liabilities should lead to increases in expected return
on common stock. In particular, changes in asset components which increase
the volatility of an institution's portfolio should lead the stock market to
upwardly revalue S&L equity. This hypothesis isexamined using data for the
July 1984-December 1987 period. Increases in commercial mortgage loans,
acquisition and development loans, direct investments, and nonmortgage
loans appear to cause higher return for shareholders of higher-risk S&Ls.
Similar increases appear to have littleimpact on the common stock returns of
lower-risk S&Ls.
F R B C H IC A G O W orking P a p e r
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1
T h e
Im p a c t
o f D e p o s it I n s u r a n c e
S h a r e h o ld e r s ’ R is k / R e tu r n
o n
S & L
T r a d e -o ffs
Elijah Brewer III*
Despite the widespread belief that under priced deposit insurance provides
incentive for insured institutions to increase the value of shareholder equity by
investing in assets that shift risk onto the deposit insurer, little, if any,
empirical evidence has been presented to testthis hypothesis. This paper tests
this hypothesis by examining the impact of changes in balance sheet
composition on savings and loan association (S&L) common stock returns.
We find, among other things, that the common stock returns of high-risk
S&Ls respond favorably to increases in commercial mortgage loans,
acquisition and development loans and nonmortgage assets, while those of
other S&Ls do not. This suggests that high-risk S&Ls have used these assets
to increase the volatility of the asset portfolio, in turn raising the value of
deposit insurance and the value of shareholders' equity.
Since the early 1980's, most S&Ls have been allowed to engage in
nonmortgage activities. Consumer lending, business lending, and direct
investment authority are examples of expanded assetpowers granted to S&Ls.
Many of the new asset powers were granted because they are thought to have
less interest-raterisk than the traditional long-term fixed-rate mortgage loans.
Research on the effects of deregulation of S&Ls has drawn considerable
interestinrecent years. Much empirical research has focused on attempting to
either predict or evaluate the effects of deregulation on S&Ls' riskiness (e.g.,
Benston [7]; Benston and Koehn [5]; FHLBB [ll] ) . 1 In the presence of an
effective deposit insurance system with early closure such studies would be
only of academic interest. However, experience has shown that deposit
insurance tends to be associated with delayed closure.2 Because of this delay,
access to underpriced deposit insurance has advantages and distressed
financial institutions quite rationally attempt to exploit those advantages.
*1 thank Herbert Baer, Rebel Cole, George Kaufman, and the participants of the finance seminar
at the Loyola University of Chicago for valuable comments and suggestions. The views
expressed here are solely those of the author and do not necessarily represent the views of the
Federal Reserve Bank of Chicago or the Federal Reserve System.
F R B C H IC A G O W orking P a p e r
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2
Benston and Koehn [4] investigate the differential portfolio behavior of lowcapital and high-capital S&Ls. They find that nonmortgage assets held by
S&Ls with low-capital were associated with higher risk as measured by the
standard deviation of stock returns, while nonmortgage assets held by S&Ls
with high-capital were not. They and others suggest that low-capital S&Ls
tend to increase the value of shareholders' common equity by gambling some
of the institutions' assets on investments with large but less likely payoffs and
a correspondingly high variance.3 To a S&L close to failure, such a gamble is
worth taking because the gamble can only increase the expected value of the
common stock. In other words, there is no downside risk to shareholders.
Should the bet fail,the shareholders are no worse offby the gamble. Should
the bet pay off, the equity holders stand togain.
This paper tests the hypothesis that financially distressed S&Ls increase the
value of shareholders' equity by investing in assets that shift risk onto the
deposit insurance. Section 1 discusses the impact of nonmortgage assets on
S&L common stock returns. Section 2 presents a model of changes in a S&L's
market value. Section 3 discusses the data and methodology. The empirical
resultsare presented in section 4. The final section contains a summary of our
findings.
T h e Im p a c t o f A s s e t - M i x o n S & L C o m m o n S to c k R e tu rn s
The effect of asset-mix investments on S&L common stock returns depends
on what investments are permitted, what assets S&Ls invest in, how mix with
other assets, and how the investments are managed. Allowing S&Ls to invest
in nonmortgage assets changes the efficientrisk/retum frontieravailable to the
S&L. The exact shape of the new frontier depends both on what investments
are permitted and how S&Ls’managers choose to operate these investments.
The Depository Institutions Deregulation and Monetary Control Act of 1980
allows S&Ls to engage, among other things, in business and consumer
lending. Commercial mortgage lending was restricted to 20 percent of assets,
as were the combined aggregate holdings of consumer loans, commercial
paper, and debt securities.4 Additional product-line deregulations were
provided in the Gam-St Germain Depository Institutions Act of 1982. In
particular, the 1982 act relaxed the quantitative restrictions on commercial
mortgage loans from 20 percent to 40 percent and broadened the array of
permissible investments to include time and savings deposits of other S&Ls
and, most importantly, business loans. In May 1983, the now defunct Federal
Home Loan Bank Board (FHLBB) permitted federal S&Ls to invest up to 11
F R B C H IC A G O W orking P a p e r
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3
percent of assets in junk bonds. During the same period, many state
governments enacted statutes that broadened asset powers for their statechartered S&Ls even more. State-chartered S&Ls were permitted by several
states to invest considerable amounts directly inreal estate,corporate equities,
and subsidiary service corporations. These direct investments have been
blamed by the FHLBB for the losses incurred by the Federal Savings and
Loan Insurance Corporation (FSLIC). And as a result, Congress, in the
Financial Institutions Reform, Recovery and Enforcement Act of 1989,
restricts the ability of S&Ls to make and hold nonmortgage assets and
requires S&Ls to raise the level of housing and housing-related loans in their
portfolio to 70 percent from the previous 60 percent level.
Table 1 examines, as of December 31, 1988, the portfolio composition of
S&Ls nationwide and each of six states (California, Florida, Illinois,
Louisiana, Oklahoma, and Texas) that have accounted for the largest share of
the total cost of allfailureresolutions from 1980 through 1988.5 In the table,
S&Ls are divided into three groups: (1 ) S&Ls with negative book equity
according to generally accepted accounting principles (GAAP); (2) lowcapital (that is, positive net worth below 6 percent of assets); and (3) wellcapitalized S&Ls (with net worth above 6 percent of assets).
The table shows that there is a substantial variation among states in
percentage of assets devoted to direct investments. Moreover, ittends to be
the insolvent firms that engage most prominently in these activities. Both
nationwide and in all 6 states, insolvent S&Ls held more direct investments
than solvent institutions. At the same time, insolvent S&Ls also held a
smaller proportion of their assets in mortgages (Oklahoma is an exception).
From these limited data, insolvent S&Ls appear to hold more of what the
FHLBB considered to be risky assets than the rest of the industry. However,
this analysis does not permit us to determine the direction of causation, as the
data provide information only on the outcomes of S&L decisions.
A change in asset composition, with or without underpriced deposit insurance,
may lead to an increase in expected return on equity. Underpriced federal
deposit insurance, however, gives S&Ls an advantage in holding risky assets
and can, in some instances, create incentives forexcessive risk-taking.
Since many depositors funds are insured, depositors do not have any incentive
to impose discipline on the use of their funds. The institutions, therefore, can
use these deposits to engage in riskier activities than would otherwise be
possible. Studies by Merton [19] and Buser, Chen and Kane [9] show that
F R B C H IC A G O W orking P a p e r
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4
providing deposit guarantees at less than their market value provides banks
with a subsidy. The value of this subsidy equals the difference between the
cost of risky and riskless (guaranteed) deposit claims less the premium
charged for insurance. Access to future deposit guarantees, under these
circumstances, is an asset of the bank. The value of this asset is equal to the
present value of the stream of subsidies the bank or S&L expects to receive.
Therefore, expansion into riskier activities may enhance S&L value because
risk-taking issubsidized.
We would, therefore, expect that financially distressed S&Ls to seek out
riskier investments to increase the possibility of a large payoff. These S&Ls
are likely to select or invent new combinations of mortgage and nonmortgage
assets that are risk-increasing. In selecting new combinations of mortgage
and nonmortgage assets, S&Ls may provide information on the riskprofile of
their asset portfolio. If the market perceived these combinations as riskier,
then the value of the option to repurchase the assets will increase along with
the value of common stock and the expected return on common stock. This
paper examines the relationship between common stock returns and changes
in asset composition and growth in liabilities to test whether the market
responds in a positive way to riskier activities for the more risky relative to
less risky institutions.
M o d e l l i n g C h a n g e s in M a r k e t V a l u e
The primary hypothesis examined in this paper is that changes in S&L
involvement in nonmortgage activities significantly influence S&L common
stock returns. The approach used to test this hypothesis is to model changes
in the market value of equity.
The market value of an S&L equity reflects the value of its net portfolio
holdings and access to underpriced deposit insurance (see Unal and Kane
[20]). That is,
M . =A* - L * + D I .
JJ
JS
j,*
(1)
where M j tis the market-value net worth of the jth S&L in period t; Ajt* is
the market value of assets of thejth S&L in period t; Lj t isthe market-value
of liabilities of the jlh S& L in period t; and DIj>t is die value of access to
deposit insurance.
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5
The market’s valuation of the assets recorded on each S&L’s book varies over
time as interestrates change and credit risk waxes or wanes. W e express the
market valuation of thejih S&L assets at time period tas proportionate to the
book value,
A* =a. A.
ut
JJ J,t
(2)
where ajjtisan appropriate mark-up or mark-down factor applied to the book
value reported by diejth S&L.
For thejth S&L, liabilitiesat time t+1 is
L* =L. (l+/f)
y,r+1 y,r
(3)
v '
where rt^ isthe ratepaid on liabilitiesin time period t.
For thejih S&L, the market value of net worth at time t+1 is
M.
= (l+r?)A*-(l
+ >f)L*+AS.
-DIV.
+D/. t+l
t J,t
x J,t
j,t
j,t+1
j,t+1 v
(4)
where DIVj
isdividend paid by thejth S&L to shareholders in period t+1;
rt^ is the market rate of return on asset portfolio in time period t;and ASj tis
new equity raised through flotation of shares during time period t.
The change in the market value of net worth is,
M.
,- M .
j,t+ 1
= AM . =
j,t
[rV
- r^L*
+AS. -DIV. ,+ AD/. 1
* j,t
t j,t
j%
t
j,t+1
j,t*
(5)
v J
Dividing both sides of (5) by Mj tand rearranging results in
R . =TT -[r * A * —rf-L* +AS. +AD/.J
J.‘ M.
• j .i
' j .‘
h‘
Jf
(6)
where Rj tisthe rate of return on the common stock.
F R B C H IC A G O W orking P a p e r
D ecem ber 1989, W P -1989-24
6
We know that deposit insurance can be viewed as an European Put option
[19]. Hence,
(7)
where oj ^ is the standard deviation of the rate of return on the asset
portfolio; and f(.)has theproperty that fj < 0 and f2 > 0 .6
Hence,
ADI.
T r H 4fc),
^
it
(8)
Jjt
it
Substituting (8 )into (6 )and rearranging resultsin
A*
f
R.
=7
- W
it M .
it
The A[A /L
]j
'
It
+AS.
* It
]+ K A —
wl
Jt
+ f A a A]-£-.
l r * J
'it
J2
j/ m
.
(9)
it
tvariable can be decomposed into the following terms
f A*\
A I
A.
_
\L')jt
tt
,
A.
jt+i ___ jt
L*,,+i
jt+ i
(10)
L*'
,t
jt
Let
L*
=(1+^JL*
v °J,r j,t
(11)
j t +1
where gj tisthe growth rateof liabilities in time period t. Then
A
(l+r,)A. +g. C +A S.
v ' jt ajrjt
jt
l;
F R B C H IC A G O W orking P a p e r
D ecem ber 1989, W P-1989-24
+i
(12)
*
7
Assuming ASjt= 0, we can rearrange these terms to get
f
r*A*
A*
g.
(13)
u ’-L ^
V
V
Now Oj t^ can be approximated by
„ A* (i)
(14)
'•*
i
1
A*
if
where A: t*(i) isthe holdings of the ijh asset at time tof thejlh S&L; and a* is
the standard deviation of the rate of return on the ijh asset.
A linearapproximation of the AatA can be written as
a
;.(o
if
(15)
A* .
jf J
Substituting (13) and (15) into (9) we get
A*
A*
a
:
+ f ,u -p
j,t
g ;t
/»*
L*
U* ]
M. +/2X
_<1+« A L
j >*
J
AS.
{A’ ii)']
a
i
(16)
M.
i
J
Equation (16) suggests that four factors affect the stock returns of an insured
institution: the return on existing assets, rt^ ; the rate on liabilities, rt^,
valued as a riskless instrument; the growth rate of liabilities; and the change in
asset volatility due to changes in asset composition. For low-risk S&Ls, fj
and f2 will be near zero because deposit insurance is presumably a relatively
unimportant source of value. This implies that the impact of liability growth
and changes in asset composition will be different for high- and low-risk
S&Ls. How stock returns change with liability growth rate depends on
F R B C H IC A G O W orking P a p e r
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8
whether the S& L is economically solvent. Flannery [13] has noted that when
a firm’s capital is positive, faster growth means lower capitalization. Lower
capitalization will lead to a rise in the value of access to deposit insurance.
And as a result, this should generate higher stock returns. For insolvent firms,
however, Flannery's simulation experiments showed that faster growth
initially generates high capital ratios because the dollar amount by which the
market value of liabilities initially exceed the market value of assets becomes
decreasingly significant We would, therefore, expect that the growth rate of
liabilities to have a positive impact on the stock returns of low-risk S&Ls and
a negative impact on the stock returns of higher-risk S&Ls. The variables
used to operationalize the factors affect S& L stock returns are discussed
below.
The Independent Variables
Since S&Ls invest primarily in mortgages, we assume that the primary factor
affecting the market’s valuation of an S& L’s assets is changes in the market
value of mortgages. The holding period returns associated with long-term
U.S. government bonds, obtained from Standard and Poor's weekly bond
index (RTBOND), are used to measure changes in the market value of
mortgages. The returns on a stock market index, RMKT, is included in the
equation to control for systematic marketwide fluctuations on the common
stock returns of individual S&Ls.
The other important factors affecting common stock returns are associated
with changes in the value of deposit insurance. Two affects must be taken
into account: the impact of the growth in liabilities, gj t, on the subsidy per
dollar of equity and changes in volatility, a j y \ on the subsidy per dollar of
equity. The growth rate of liabilities is captured by the variable LIBGROW.
LIBGROW should capture the impact of increased leverage on the value of
deposit insurance and shareholders' common stock returns and is expected to
have a positive sign. The impact of changes in volatility is captured less
directly.
Conceptually, if a S&L holds a portfolio of mortgage and nonmortgage assets
of different risks/retums, then, as the relative investment in the different assets
changes, the volatility of the S&L's asset returns must change. The precise
behavior of volatility as a function of the asset mix will depend on the relative
riskiness of the different asset categories; changes in asset mix can either
increase or decrease common stock returns.
Two potentially important
sources of influence of S&L's asset volatility are the ratio of the change in
F R B C H IC A G O W orking P a p e r
D ecem ber 1989, W P-1989-24
9
direct investments to market value of common stock (DDIRECT) and the ratio
of the change in nonmortgage loans to market value of common stock
(DNONMORT). Changes in the relative investment in these different assets
will change S&L common stock returns. The change in other assets divided
by the market value of common stock (DOASSET) is included in the equation
to control for other asset categories that may influence S&L common stock
returns. The other asset category, net of contra-assets, includes (1) foreclosed
real estate and real estate held in judgement; (2) office, furniture, and
equipment (3) investment securities (including junk bonds); and (4) all other
asset categories.
Two mortgage asset categories are also employed: traditional fixed-rate
mortgages and adjustable-rate mortgages. We would expect that returns on
direct investments and nonmortgage loans would be more volatile than fixedand adjustable-rate mortgages. Thus over the course of, say, a quarter
changes in portfolio composition away from traditional assets toward higher
risk nontraditional assets should lead to an increase in asset volatility and an
one time positive return to shareholders. This effect will only be important
for those institutions for whom deposit insurance is an important balance sheet
component
Changes in the following asset portfolio items are employed:
fixed-rate
mortgages (DFRM); adjustable-rate mortgages (DARM); direct investments
(DDIRECT); nonmortgage loans (DNONMORT); and other assets
(DOASSET).
The resulting empirical equation is,
+ a D O A S S E T . -f co.
6
Jj.t
,t
Jj,‘
,
(17)
where C0j t is a stochastic error term. Estimation of equation (17) allows us to
investigate the equity market response to risky activities.
Much of the concern about S&L nonmortgage activity deregulation has to do
with high-risk S&Ls gambling some of the institutions' assets on investments
with large but likely payoffs. In order to examine this issue, the S&Ls in this
F R B C H IC A G O W orking P a p e r
D ecem ber 1989, W P-1989-24
10
study are ranked according to their risk-of-failure.
Risk-of-failure is
measured as the sum of one plus the mean return on common stock divided by
the standard deviation of the rate of return on common stock. Intuitively, the
risk-of-failure is an estimate of the number of standard deviations below the
mean that the return on common stock would have to fall so as to render
equity negative. Negative equity is one common definition of failure. High
probability of failure is associated with high standard deviation of common
stock returns, low mean returns, and low capitalization ratios.
The sample of S&Ls was ordered by risk-of-failure and divided into three
groups:
high-risk, medium-risk, and low-risk.7
The high-risk category
includes the first forty percent of S&Ls that had the highest risk-of-failure
values. The medium-risk category includes the next twenty percent of S&Ls
that had the highest risk-of-failure values. The low-risk category is comprised
of the remaining forty percent of S&Ls in the sample.
D a ta an d M e th o d o lo g y
The data used in this paper are for 63 S&Ls whose stock was traded on the
New York Stock Exchange, American Stock Exchange, or Over the Counter
and which filed FHLBB R eport o f Condition data for each quarter over the
July 1984-December 1987 sample period.
Stock market data are from
Interactive Data Services, Inc. For multiple S&L holding companies, the
assets of individual S&L subsidiaries were summed in constructing the
balance sheet variables discussed below.8
Table 2 shows the total assets for each of the 63 S&Ls at year-end 1987. O f
the 63 S&Ls in the sample, 18 had total assets of more than S5 billion. There
were 26 S&Ls with total assets between $1-5 billion. The remaining 19 S&Ls
had total assets less than $1 billion. At the end of 1987, the 63 S&Ls had
$303 billion in total assets. Expressed as a percentage of the industry's asset
total, sample S&Ls constitute about 31 percent
Common stock returns over a quarter were calculated by averaging weekly
common stock returns. The returns are dividend-unadjusted.9 The holding
period return on long-term U. S. government bonds is used to measure
changes in the market value of mortgages. The stock market portfolio
employed in this study is the S&P500 market index.
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11
The liability variable (LIBGROW) is estimated as the quarter to quarter
percent change in total S& L liabilities. The fixed-rate mortgage loans-tocapital ratio (DARM) was computed by taking the change in fixed-rate
mortgage loans and dividing by total market value of common stock. The
market value of common stock is calculated by multiplying the number of
shares outstanding at the end of each quarter by the price of the S&L's
common stock at the end of the quarter. An S&L's involvement with direct
investments (DDIRECT) is measured by the ratio of the change in direct
investments to S&L market value of common stock. Direct investments
include equity securities (except Federal Home Loan Bank Stock), real estate
investments, and investments in service corporations or subsidiaries. The
nonmortgage loan ratio (DNONMORT) is the change in the sum of total
business and consumer loans divided by S&L market value of common
stock.10 The other asset ratio (DOASSET) is the change in other assets not
elsewhere classified divided by S& L market value of common stock.11 The
sample period covers 14 quarters beginning in 1984:3 and ending in 1987:4.
The samples of high- and low-risk S&Ls are each represented by 26
associations with a pooled cross-sectional time-series data of 364
observations.
The medium-risk group of S&Ls is comprised of 12
associations with a combined 154 observations. Table 3 depicts the mean
portfolio composition of selected variables over the sample period by risk
category. The table also presents the differences between high- and low-risk
S&Ls in the means for each of the variables and the corresponding t-statistics
of the differences. High-risk S&Ls have more adjustable-rate mortgage loans,
commercial mortgage loans, acquisition and development loans, and deposit
plus Federal Home Loan Bank advances than low-risk S&Ls. Low-risk S&Ls
have more residential mortgage loans and nonmortgage loans.
Our methodology involves first stacking the equations for the three risk
classes of S&Ls and estimating the relation between S& L stock returns and
the balance sheet variables. Next, we examine only the differential response
of high- and low-risk S&Ls. In this stage the medium-risk group is eliminated
because it serves as a buffer to allow an S&L to shift out of high (low)-risk
without being immediately reclassified as low (high)-risk.
The first step in analyzing the valuation effects of nonmortgage assets is to
estimate the following model (see Table 4)
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12
rr .
R
M
= P0+ $ ]R M K T + $ 2R T B O N D
L*LJ
rz
r[ A H A M ^ l ]
H
0
0
0
Z
M
0
0‘
0
+ £
(18)
z ,_
where Z jj, Zj^, and Z^ are the vectors of balance sheet variables for highrisk, medium-risk, and low-risk S&Ls, respectively; A jj, Aj^, and A ^ are
coefficient vectors for the three risk classes; and e is an error term.
E m p ir ic a l R e s u lts
The results of the estimation of equation (18) using ordinary least squares
(OLS) regression are shown in Table 5.
The estimated values of the
parameters represent their cross-sectional average values.
The results in Table 5 indicate that both the returns on the stock market index
and the holding period returns on long-term U.S. government bonds are
statistically significant in explaining S& L common stock returns. For every
100 basis point change in stock market returns, S& L common stock returns
will change, on average, 133 basis points. For every 100 basis point change in
holding period returns, S&L common stock returns will change, on average,
57 basis points.
The liability growth rate term has the expected effect on common stock
returns of S&Ls. This variable is negative and significant for high-risk S&Ls
and positive for medium- and low-risk S&Ls but is only significantly different
from zero for the medium-risk group. I3
The stock market responds
unfavorably to rapid growth at high-risk S&Ls because growth generates
higher market capitalization. However, the stock market responds favorably
to rapid growth in liabilities at medium- and low-risk S&Ls.
For high-risk S&Ls, common stock returns increase significantly with growth
in direct investments (DDERECT), nonmortgage assets (DNONMORT), and
other assets (DO AS SET). None of the balance sheet variables have a
statistically significant impact on the common stock returns of medium- and
F R B C H IC A G O W orking P a p e r
D ecem ber 1989, WP-1989-24
13
low-risk S&Ls. In this regression equation, the positive and statistically
significant coefficients on DDIRECT, D N O NMORT, and DOASSET and the
insignificant coefficients on mortgage assets suggest that shifts in S&L
investment strategies from traditional low-risk to nontraditional high-risk
activities enhance returns to equity holders of high-risk S&Ls. Table 6 tests
for differences in coefficients between D F R M and DDIRECT, D N O N M O R T ,
DOASSET, and DARM. With the exception of DARM, the high-risk S&L
coefficients on DDIRECT, DNONMORT, and DOASSET are all significantly
greater than that on DFRM, implying that the stock market reacts favorably to
shifts in those firm’s investment strategy from low-risk to high-risk assets.
The separate empirical results for high- and low-risk S&Ls are presented in
Table 7. Zellner’s [21] seemingly unrelated regression techniques are used to
estimate these equations. The results show that the stock market risk
sensitivity of high-risk S&Ls is fifty percent more than that of low-risk S&Ls.
The coefficient difference is statistically significant at the 0.01 level.
Evidently, the stock market perceived that high-risk S&Ls are more exposed
to marketwide movements than low-risk associations. The interest rate
sensitivity coefficient of high-risk S&Ls is twenty percent less than that of
low-risk associations.
This coefficient difference__is not statistically
significant, however. Also, noteworthy is the fact the R^ is lower for highrisk S&Ls than low-risk S&Ls, suggesting that nonsystematic risk is higher.
The relationships between S&L common stock returns and fixed- and
adjustable-rate mortgages, direct investments, nonmortgage assets, and other
assets are consistent with those reported in Table 5. In particular, the stock
market reacts favorably to increases in DDIRECT, D N O NMORT, and
DOASSET of high-risk S&Ls.14 The low-risk S&L results reported in Table
7 show little evidence of a statistically significant association between
nonmortgage activities and common stock returns. The liability growth rate
term isnot significantly different from zero for both high- and low-risk S&Ls.
Tests were conducted for each group of S&Ls to examine the differences in
the coefficients between D F R M and DDIRECT, D N O NMORT, and
DOASSET. These tests are reported in Table 8 . The results indicate that the
coefficients of DDIRECT, DNONMORT, DOASSET are significantly greater
than the coefficient of D F R M for the high-risk S&Ls.
Two additional tests were conducted. The first examines whether one-period
lagged changes in balance sheet variables have any additional informational
content that is not already captured by current changes in the variables. The
F R B C H IC A G O W orking P a p e r
D ecem ber 1989, W P -1989-24
14
empirical results indicate that none of the lagged terms have a statistically
significant positive impact on high-risk S&L common stock returns (The null
hypothesis that coefficients are all equal to zero cannot be rejected [Fg 3 4 9 =
1.2133]).15 This result suggests that current variables capture ?'pure"
announcement effects on S&L stock returns. The second set of tests examines
whether G A A P net worth insolvent high-risk institutions have coefficients
different than those for solvent high-risk S&Ls. 16 The null hypothesis that
coefficients are equal for the two groups can be rejected at the 0 .0 1 level
^6,349 =3-8930).
Alternative Decomposition of the Mortgage Portfolio
In this section, we employ an alternative decomposition of the mortgage
portfolio. In particular, the mortgage portfolio is divided into four categories:
residential mortgage loans (RMORT), commercial mortgage loans (CMORT),
acquisition and development loans (ADL), and other mortgage assets
(OMORT) which include multifamily mortgage loans and mortgage-backed
securities. During the early 1980s S&Ls were given broader powers to hold
commercial mortgage loans. If S&Ls altered the composition of their
mortgage assets (moving, for example, from residential mortgage loans to
commercial mortgage loans), this may have a similar favorable impact on
S&L stock returns as shifts from traditional mortgage loans to nontraditional
nonmortgage assets. W e would expect that returns on commercial mortgage
loans and acquisition and development loans would be more volatile than the
returns on residential mortgage loans.
The implications of this alternative decomposition of the mortgage portfolio
may be modelled as follows
R
= 3rt+ $ ,R M K T + & R T B O N D + h L I B G R O W . + & D R M O R T
jjt r 0
rl
t r2
t
1
J%t
2
j,t
+ 8 D C M O R T . +8 D A D L . + S D O M O R T . + & D D IR E C T .
3
J, I
4
J ,l
5
6
+ 8p N O N M O R T . + 8sD O A S S E T . + v . f
J,t
(19)
where D R M O R T is the change in residential mortgage loans divided by S&L
market value of common stock; D C M O R T is the change in commercial
mortgage loans divided by market value of common stock; D A D L is the
change in acquisition and development loans divided by market value of
common stock; D O M O R T is the change in other mortgage assets divided by
F R B C H IC A G O W orking P a p e r
D ecem b er 1989, W P -1989-24
15
market value of common stock; and x>\t is a stochastic error term. Equation
(19) is estimated for high- and low-risk S&Ls over the July 1984-December
1987 period using Zellner's [21] seemingly unrelated regression techniques.
The results are presented in Table 9. For both high- and low-risk S&Ls the
sign and significance pattern of the variables measuring direct investment,
nonmortgage loans, and other assets are quite similar to those reported in
Table 7. O f the four mortgage-mix variables, only two are significant and
positive for high-risk S&Ls: commercial mortgage loans (DCMORT) and
acquisition and development loans (DADL). Surprisingly, the coefficient of
AD L for low-risk S&Ls is significant and negative.
Tests were conducted for each group of S&Ls to examine the differences in
the coefficients between DRMORT and DCMORT, DOMORT, DADL,
DDIRECT, DNONMORT, and DOASSET. These tests are presented in
Table 10. The results indicate that the coefficients of DCMORT, DADL,
DDIRECT, DNONMORT, and DOASSET are significantly greater than the
coefficient of DRMORT for the high-risk S&Ls.
The high-risk S&L results indicate that the stock market responded favorably
to shifts in mortgage assets from residential mortgage loans to commercial
mortgage loans and acquisition and development loans. Barth and Bradley [3]
find that within the mortgage category, insolvent institutions have
dramatically and rapidly increased their commercial mortgage lending. Barth,
Bartholomew, and Labich [2] present evidence indicating that acquisition and
development loans have a positive and statistically significant effect on
resolution costs. These results, coupled with the evidence that the stock
market responded positively to increased risk-taking, support the view that
federal deposit insurance created a moral hazard problem.
Overall, the above results point out, especially for the high-risk S&Ls, that
changes in nontraditional mortgage and nonmortgage activities tend to lead to
higher common stock returns. If, as many believe, deposit insurance is
subsidized, high-risk federally-insured institutions may be more likely to
receive government subsidies through underpriced insurance premiums than
low-risk firms. The empirical results for high-risk S&Ls support this point.
In the presence of underpriced deposit insurance, changes in both
nontraditional mortgage and nonmortgage activities at high-risk S&Ls will
tend to raise common stock returns. An important implication of this result is
that under a system of deposit insurance which allows insolvent firms to
F R B C H IC A G O W orking P a p e r
D ecem ber 1989, W P -1989-24
16
remain open, increases in nontraditional and nonmortgage assets will raise
common stock returns since risk-taking is borne mainly by the deposit insurer.
Sum m ary
This study tests the hypothesis that deposit insurance has distorted
shareholders' risk/retum trade-offs for financially distressed S&Ls. S& L
common stock returns were regressed on a market returns index, a bond
returns index, liability growth rates, traditional mortgage loans, nontraditional
mortgage loans, direct investments, nonmortgage (business plus consumer)
loans, and other assets as a percent of market value of common stock. The
differential behavior of high-risk S&Ls compared to low-risk S&Ls was
analyzed. Shifts from traditional mortgage loans to more volatile commercial
mortgage loans, acquisition and development loans, direct investments, and
nonmortgage (business plus consumer) loans tend have a favorable impact on
the common stock returns of high-risk S&Ls. These results support the
concerns of many that the current system of deposit insurance provides
incentives for a high-risk S&L to shift the firm's investment strategy from
low-risk to high-risk projects.
This study provides the first empirical evidence that financial markets
responded positively to announcements of increased risk-taking.
Taken
together with evidence that S&Ls at risk of failure actually invested more
heavily in these high-risk activities, this paper suggests that the losses at
S&Ls in the late 1980s were the result of a deliberate management policy to
pursue high-risk strategies. These strategies were only made possible by a
combination of inept supervision, lax closure policy, and deposit insurance
guarantees.
F R B C H IC A G O W orking P a p e r
D ecem ber 1989, W P -1989-24
17
R e fe r e n ce s
[1] Barth, James R., Philip F. Bartholomew, and Michael G. Bradley. "The
Determinants of Thrift Institution Resolution Costs." Research Paper No. 89OS, Office of the Chief Economist, Office of Thrift Supervision, (November
1989).
[2] Barth, James R., Philip F. Bartholomew, and Carol Labich.
"Moral
Hazard and the Thrift Crisis: An Analysis of 1988 Resolutions." Proceedings
o f a Conference on Bank Structure and Competition, Federal Reserve Bank of
Chicago, 1990.
[3] Barth, James R., and Michael G. Bradley. "Thrift Deregulation and
Federal Deposit Insurance."
Journal o f Financial Services Research
2(September 1989), pp. 231-259.
[4] Barth, James R., R. Dan Brumbaugh, Jr., Daniel Sauerhaft, and George H.
K. Wang.
"Thrift Institution Failures: Causes and Policy Issues."
Proceedings o f a Conference on Bank Structure and Competition, Federal
Reserve Bank of Chicago, 1985, pp. 184-216.
[5] Benston, George J., and Michael F. Koehn.
"Capital Dissipation,
Deregulation, and the Insolvency of Thrifts." Unpublished paper (June 1989).
[6] Benston, George J. and George G. Kaufman.
Risk and Solvency
Regulation of Depository Institutions: Past Policies and Current Options.
Monograph Series in Finance and Economics, Salomon Brothers Center for
the Study of Financial Institutions, (1988).
[7] Benston, George J. An Analysis o f the Causes o f Savings and Loan
Association Failure. Monograph Series in Finance and Economics, Salomon
Brothers Center for the Study of Financial Institutions, (1985).
[8] Brickley, James A. and Christopher M. James. "Access to Deposit
Insurance, Insolvency Rules and the Stock Returns of Financial Institutions."
Journal o f Financial Economics 16(July 1986), pp. 345-371.
[9] Buser, Stephen A., Andrew H. Chen and Edward J. Kane. "Federal
Deposit Insurance, Regulatory Policy and Optimal Bank Capital." Journal o f
Finance 36(March 1981), pp. 51-60.
F R B C H IC A G O W orking P a p e r
D ecem ber 1989, W P-1989-24
18
[10] Calomiris, Charles W.
"Do 'Vulnerable' Economies Need Deposit
Insurance? Lessons From the U. S. Agricultural Boom and Bust of 1920s."
WP-89-18, Issues in Financial Regulation, Federal Reserve Bank of Chicago,
(October 1989).
[11] Federal Home Loan Bank Board. "Net Worth Requirements of Insured
Institutions." 12 CFR Parts 561, 563, 570, 571, and 584, proposed rule,
Federal Register 49(December 7,1984), pp. 47852-47870.
[12] Furlong, Frederick T., and Michael C. Keeley. "Capital Regulation and
Bank Risk-taking: A Note." Journal o f Banking and Finance, Forthcoming.
[13] Flannery, Mark J. "Recapitalizing the Thrift Industry." Proceedings o f
the Eleventh Annual Conference, Federal Home Loan Bank of San Francisco,
1985, pp. 91-113.
[14] Flannery, Mark J., and Christopher James. "The Effect of Interest Rate
Changes on the Common Stock Returns of Financial Institutions." Journal o f
Finance 39(September 1984), pp. 1141-1153.
[15] Giliberto, Michael. "Interest Rate Sensitivity in the Common Stocks of
Financial Intermediaries: A Methodological Note." Journal o f Financial and
Quantitative Analysis 20(March 1985), pp. 123-126.
[16] Kane, Edward J. The Gathering Crisis in Federal Deposit Insurance.
MIT Press, Cambridge, MA, 1985.
[17] Keeley, Michael C., and Frederick T. Furlong. "A Reexamination of
Mean-Variance Analysis of Bank Capital Regulation." Journal o f Banking
and Finance, Forthcoming.
[18] Lynge, Morgan J., and J. Kenton Zumwalt. "An Empirical Study of the
Interest Rate Sensitivity of Commercial Bank Returns: A Market Index
Approach." Journal o f Financial and Quantitative Analysis 15(September
1980), pp. 731-742.
[19] Merton, Robert C.
"Analytical Derivation of the Cost of Deposit
Insurance and Loan Guarantees: An Application of Modem Option Pricing
Theory." Journal o f Banking and Finance l(June 1977), pp. 3-11.
F R B C H IC A G O W orking P a p e r
D ecem ber 1989, WP-1989-24
19
[20] Unal, Haluk, and Edward J. Kane. "Off-Balance-Sheet Items and the
Changing Market and Interest-Rate Sensitivity of Deposit-Institution Equity
Returns." Proceedings o f a Conference on Bank Structure and Competition,
Federal Reserve Bank of Chicago, 1987, pp. 432-455.
[21] Zellner, Arnold. "An Efficient Method of Estimating Seemingly
Unrelated Regressions and Tests for Aggregation Bias." Journal o f the
American Statistical Association (1962),pp. 348-364.
F R B C H IC A G O W orking P a p e r
D ecem ber 1989, W P-1989-24
20
F o o tn o te s
1A rather thorough study by Barth, Brumbaugh, Sauerhaft, and Wang [4] examines the
factors influencing the costs to the insurance fund when a S&L fails.
^Barth, Bartholomew, and Labich [2] present evidence showing that a substantial
number of the 205 resolved thrifts in 1988 had been insolvent since the early 1980s.
Resolution refers to liquidation or assisted merger. Using data from an earlier period,
Calomiris [10] finds that the time delays for liquidation of insured institutions were
much longer than of uninsured firms.
^See, for example, Barth, Bartholomew, and Bradley [1]; Barth, Bartholomew, and
Labich [2]; Kane [15]; and Furlong and Keeley [12].
^See Barth and Bradley [3] for an excellent discussion of regulatory and legislative
developments for 1980 through 1988.
^See Barth, Bartholomew, and Labich [2].
6For large [Aj>t/Lj#t], f^ < 0.
^Alternatively, the sample of S&Ls was divided into equally sized categories with little
change in the basic results.
^For each of the holding companies included, the S&Ls were the major activity of the
holding company in terms of assets. The mean ratio of S&L assets to total company
assets was 97.9 in 1987. Other holding company activity included real estate property
management; housing development; brokerage services; insurance products; data
processing services; corporate debt and equity securities; and real estate appraisal
services. Assets for the holding companies were obtained from Moody’s Banking and
Finance Manual.
^S&L stock returns are dividend-unadjusted because the S&P500 market index
excludes dividends. This omission might result in not finding any impact on S&L
stock returns of shifts from low-risk to high-risk assets. To the extent that we are able
to find such an impact provides a strong test of our hypothesis.
l^The definitions of direct investments and nonmortgage loans are identical to those
used by Barth, Bartholomew, and Bradley [1].
1 *Junk bonds are included in this asset category.
l^The simple correlation coefficient between RMKT and RTBOND is 0.34 and is
statistically significant from zero. Because these two factors exhibit some degree of
multicollinearity, previous studies have suggested that an orthogonalization procedure
be used to remove this multicollinearity (see Lynge and Zumwalt [18] and Flannery
and James [14]). This procedure orthogonalizes changes in RTBOND by regressing
changes in RTBOND against RMKT (or RMKT against changes in RTBOND).
However, Giliberto [15] has shown that both approaches can generate bias in the tstatistics against interest rate sensitivity (market beta) depending on the causality
assumed in the orthogonalizating procedure.
Consequently this paper uses
unorthogonalized RTBOND.
An additional test was conducted to examine the relationship between S&L stock
returns and the market return index, bond index, growth in brokered deposits, and
growth in other liabilities. The results indicates that the stock market does not appear
F R B C H IC A G O W orking P a p e r
D ecem ber 1989, W P-1989-24
21
to respond to growth in either brokered deposits or other liabilities. These results are
available from the author on request.
^Recall that direct investment is the sum of equity securities (except Federal Home
Loan Bank Stock), real estate investments, and equity investments in service
corporations or subsidiaries. We re-estimated the equations using the individual
components of direct investment rather than the composite variable.
Equity
investments in service corporations appear to be responsible for the positive and
significant coefficient of the composite variable. These results are available from the
author on request.
^However, for low-risk S&Ls, the one-period lagged DARM has a positive and
significant impact on stock returns. The contemporaneous term has an identical but
negative impact on stock returns of low-risk S&Ls. These results are available from
the author on request.
l^The equation below is representative of these tests:
R = -0.0077+ 1.6074RMKT + 0.4661RTBOND
(5.558) (10.797)
(2.554)
- 0.0077UBGROWS + 0.0002DFRMS - 0.0004DARMS
(0.293)
(0.357)
(0.789)
+ 0.0020DDIRECTS + 0.0036DNONMORTs
(1.914)
(3.295)
+ 0.0011DOASSETs - O^bUBG ROW ^
(2.363)
(0.313)
+ 0.0006DFRMis + O.OOOO^ARM^
(0.716)
(0.053)
+ 0.0041DDIRECT^ + 0.0260DNONMORTis
(1.682)
(4.207)
+ 0.0005DOASSETis
(1.272)
bounded to zero.
for which R^ = 0.3654; N = 364; the subscript (s) refers to those high-risk S&Ls with
GAAP net worth greater than zero; and the subscript (is) refers to those with GAAP net
worth less than or equal to zero. The GAAP insolvent high-risk S&Ls’ coefficients of
direct investments and nonmortgage loans are greater than those for solvent high-risk
S&Ls.
F R B C H IC A G O W orking P a p e r
D ecem ber 1989, W P-1989-24
22
Table 1
Asset composition for ail FSLIC-insured institutions as of December 31,1988
Net worth
Category
Net
Commercial
mortgages1
loans
Consumer
loans
Liquid
assets2
Equity
securities
Direct
investments
Deferred
losses3
Intangible
assets
(Percent of total assets)
Total
industry
Less than or = to 0%
Between 0 and 6%
Greater than 6%
Total industry
61.2
68.8
74.8
69.7
2.6
2.9
1.3
2.5
5.7
4.7
4.0
4.6
12.0
13.2
12.7
13.0
0.2
0.3
0.5
0.3
8.9
3.4
1.8
2.8
1.3
0.2
0.1
0.2
2.5
1.8
1.5
1.8
California
Less than or = to 0%
Between 0 and 6%
Greater than 6%
Total state
63.2
74.6
82.1
75.4
0.6
4.2
0.0
3.6
0.9
2.7
1.2
2.5
21.3
10.0
8.5
10.0
0.1
0.1
0.3
0.1
6.4
3.1
1.9
3.0
0.2
0.0
0.0
0.0
0.4
1.1
2.7
1.3
Florida
Less than or = to 0%
Between 0 and 6%
Greater than 6%
Total state
65.3
67.2
74.3
68.3
2.4
2.7
1.1
2.4
8.3
6.8
4.0
6.4
11.2
13.7
12.1
13.2
0.1
0.6
0.7
0.6
6.2
2.4
2.0
2.6
0.6
0.2
0.0
0.2
0.3
2.0
3.0
2.1
Illinois
Less than or = to 0%
Between 0 and 6%
Greater than 6%
Total state
69.4
70.2
73.1
72.1
0.4
0.4
0.4
0.4
5.0
4.0
3.9
4.1
14.3
15.6
13.6
14.9
0.0
0.2
0.3
0.2
2.0
1.4
1.1
1.4
3.0
0.5
0.0
0.6
2.1
3.6
0.5
2.3
Louisiana
Less than or - to 0%
Between 0 and 6%
Greater than 6%
Total state
61.4
67.6
68.1
66.1
1.8
0.3
0.2
0.7
6.7
4.1
5.9
5.4
9.9
12.8
8.5
10.7
0.2
1.4
0.2
0.7
6.5
3.9
11.6
7.0
1.6
0.5
0.1
0.7
0.7
6.1
3.1
3.7
Oklahoma
Less than or = to 0%
Between 0 and 6%
Greater than 6%
Total state
67.3
61.9
45.7
59.2
0.5
1.3
0.7
1.1
9.3
4.3
2.6
4.4
7.6
20.6
23.8
20.1
0.4
0.2
1.9
0.6
10.7
6.9
9.9
7.8
0.3
0.0
-0.0*
0.0
0.0
1.4
8.4
2.6
Texas
Less than or = to 0%
Between 0 and 6%
Greater than 6%
Total state
51.0
46.5
53.5
48.2
3.3
2.1
1.3
2.4
3.4
2.5
8.4
3.0
11.3
24.1
21.6
20.0
0.1
0.1
0.7
0.1
19.4
15.6
5.2
16.4
0.2
0.2
0.1
0.2
4.4
1.6
2.8
2.5
1Mortgage loans, contracts, and pass-through securities net of contra-assets.
2Cash, deposits, and investment securities (excluding equity securities).
3Negative amount indicates deferred gains.
* Rounded to zero.
Table 2
Savings and loan organizations
Large S&Ls
Ahmanson H.F. and Co.
Atlantic Financial Federal
Calfed, Inc.
Carteret Savings Bank F.A.
Columbia Savings and Loan Association
Financial Corp. of Santa Barbara
First Federal of Michigan
Florida Federal Savings and Loan Association
Gibraltar Financial Corp.
Glenfed Inc.
Golden West Financial Corp.
Great American First Savings Bank
Great Western Financial Corp.
Home Federal Savings and Loan Association
Homestead Financial Corp.
Imperial Corporation of America
Transcapital Financial Corp.
Western Savings and Loan Association
Asset size
end of 1987
(in millions)
$30,533
6,703
23,443
5,947
10,059
5,360
11,524
5,496
14,984
22,470
12,894
11,845
27,642
14,150
5,423
10,886
5,746
6,053
Medium-sized S&Ls
Altus Bank
American Savings and Loan Association of Florida
Atlantic Federal Savings and Loan Association
of Fort Lauderdale
Broadview Financial Corp.
Buckeye Financial Corp.
Citadel Holding Corp.
Citizens Savings Financial Corp.
Coast Federal Savings and Loan Association, Sarasota
Collective Federal Savings Bank
Commonwealth Savings and Loan Association
Downey Savings and Loan Association
Far West Financial Corp.
First Columbia Financial Corp.
First Federal Savings and Loan Association
of Austin, Texas
First Western Financial Corp.
F R B C H IC A G O W orking P a p e r
D ecem b er 1989, W P-1989-24
$2,706
3,013
1,930
1,887
1,251
3,848
3,005
1,185
1,992
1,541
3,212
3,757
2,862
1,036
1,272
24
Table 2 (continued)
Savings and loan organizations
Medium-sized S&Ls
Great Lakes Bancorp.
Great Southern Federal Savings Bank
Investors Savings Bank
Mercury Savings and Loan Association
Metropolitan Financial Corp.
Nafco Financial Group, Inc.
Old Stone Corp.
Sooner Federal Savings and Loan Association
Valley Federal Savings and Loan Association
Washington Federal Savings and Loan Association
Western Federal Savings and Loan Association,
Marina Del Rey, California
Asset size
end of 1987
(in millions)
$3,143
1,005
2,069
2,379
2,281
1,566
4,387
1,452
3,308
1,898
2,188
Small S&Ls
American Century Corp.
American Federal Savings and Loan Association,
Colorado Springs
Charter Federal Savings and Loan Association
Continental Federal Savings and Loan Association
Cypress Savings Association
Financial Security Savings and Loan Association
Firstcorp Inc.
Frontier Savings Association
Germania, F.A.
Great Western Savings Bank
Hawthorne Financial Corp.
Home Federal Savings and Loan Association of Meridian
Home Federal Savings Bank
Local Federal Savings and Loan Association
North Carolina Federal Savings and Loan Association
Progressive Savings and Loan Association
Savers, Inc.
Virginia First Savings Bank F.S.B.
Wesco Financial Corp.
FRB CHICAGO Working Paper
December 1989, WP-1989-24
$818
842
897
716
202
190
689
347
779
831
859
79
191
810
660
559
937
471
351
25
Table 3
Com position of selected a sse ts and liabilities
Averages (September 1984-December 1987)
Item
Highrisk
Mediumrisk
Lowrisk
Difference1
T
values
(Deposit plus FHLB advances)/Total assets
0.8545
0.8285
0.8290
0.0255
4.22***
Broker deposits/Total assets
0.0552
0.0529
0.0445
0.0107
1.66
Fixed-rate mortgage loans/Total loans
0.3977
0.4193
0.4165
-0.0188
1.52
Adjustable-rate mortgage loans/Total loans
0.3341
0.3014
0.2861
0.0480
3.54***
Direct investments/Total assets
0.0321
0.0285
0.0287
0.0034
0.94
Nonmortgage loans/Total assets
0.0457
0.0582
0.0581
-0.0124
2.93***
Commercial mortgage loans/Total assets
0.1280
0.0898
0.1022
0.0258
4.06***
Residential mortgage loans/Total assets
0.3888
0.4258
0.4105
-0.0217
2.34**
Acquisition and development loans/Total assets
0.0484
0.0206
0.0293
0.0191
3.66***
Other mortgage loans/Total assets
0.2176
0.2158
0.2110
0.0066
0.82
1The difference measures the value reported for the high-risk group less that for the low-risk group.
“ Significant at the 5 percent level.
‘“ Significant at the 1 percent level.
FRB CHICAGO Working Paper
December 1989, WP-1989-24
26
Table 4
Variables used in regression equations (17), (18), and (19)
R
Quarterly average o f weekly returns unadjusted for dividends.
RMKT
Quarterly a v e r a g e of weekly returns on S&P 500 stock index.
RTBOND
Quarterly average of weekly holding period returns on U.S.
government securities.
LIBGROW
Quarterly growth rate in liabilities.
DFRM
Change in outstandings of fixed-rate mortgage loans divided by
market value of common stock.
DARM
Change in outstandings of adjustable-rate mortgage loans divided
by market value of common stock.
DDIRECT
Change in direct investments divided by market value of common
stock.
DNONMORT
Change in nonmortgage loans divided by market value of common
stock.
DRMORT
Change in outstandings of one-to-four-family mortgage loans divided
by market value of common stock.
DCMORT
Change in commercial mortgage loans divided by market value of
common stock.
DADL
Change in acquisition and development loans divided by market
value of common stock.
DOMORT
Change in other mortgage assets (including mortgage-backed
securities and other mortgage loans) divided by market value of
common stock.
FRB CHICAGO Working Paper
December 1989, WP-1989-24
27
T able 5
The response of S& L stock returns to changes In asset com ponents1
Three risk c la sse s
-0.0057
CONSTANT
(8.065)***
1.3300
RMKT
(17.965)***
0.5687
RTBOND
(6.232)***
High-risk S&Ls
LIBGROW
DFRM
DARM
DDIRECT
0.0875
0.0037
(1.944)**
(1.958)**
(0.240)
0.0004
-0.0015
0.0004
(1.396)
(1.212)
(0.826)
0.0002
-0.0014
0.0003
(0.932)
(1.072)
(0.560)
0.0023
-0.0026
0.0004
(1.146)
(0.214)
-0.0018
-0.00002
(0.712)
(0.011)
0.0010
-0.0014
0.0002
(4.912)***
(1.227)
(0.505)
0.0049
(6.680)***
DOASSET
R2
F
N
Low-risk S&l
-0.0286
(3.438)***
DNONMORT
Medium-risk S&Ls
0.3574
25.50
882
1Numbers In parentheses below the regression coefficients are the absolute value of the
corresponding t-ratios.
2Rounded to zero.
“ Significant at the 5 percent level.
‘“ Significant at the 1 percent level.
FRB CHICAGO Working Paper
December 1989, WP-1989-24
28
Table 6
T ests for the equality of asse t coefficients
with that on DFRM (F-statistics)
Using Table 5 coefficients
Variable
High-risk S&Ls
Medium-risk S&Ls
Low-risk S&Ls
DARM
0.2934
0.0093
0.0496
DDIRECT
6.8685**
0.1593
0.0001
33.9536**
0.0049
0.1244
3.5979*
0.0078
0.1450
DNONMORT
DOASSET
‘Significant at the 10 percent level.
“ Significant at the 1 percent level.
FRB CHICAGO Working Paper
December 1989, WP-1989-24
29
Table 7
Seem ingly unrelated regression results of the response of S& L stock
returns to changes in asset com ponents1
High- and low-risk S& Ls
Equation
High-risk S&Ls
Low-risk S&Ls
-0.0088
(6.333)***
-0.0028
(3.885)***
1.6059
(10.620)***
1.0727
(14.301)***
RTBOND
0.4691
(2.539)***
0.5893
(6.336)***
LIBGROW
-0.0078
(0.384)
0.0009
(0.844)
DRFM
0.0003
(0.706)
0.0001
(0.180)
DARM
0.0003
(0.744)
-0.0004
(1.158)
DDIRECT
0.0022
(2.527)***
-0.0002
(0.134)
DNONMORT
0.0049
(5.063)***
-0.0004
(0.600)
DOASSET
0.0008
(3.163)***
0.0001
(0.329)
R2
0.3344
0.4261
CONSTANT
RMKT
F
23.798
The weighted R-square for the system = 0.3960
34.683
1Numbers in parentheses below the regression coefficients are the absolute value of the
corresponding t-ratios.
•“ Significant at the 1 percent level.
FRB CHICAGO Working Paper
December 1989, WP-1989-24
30
Table 8
T e sts for the equality of asset coefficients
with that on DFRM (F-statlstics)
Using Table 7 coefficients
Variable
High-risk S&Ls
Low-risk S&Ls
DARM
0.0006
1.9739
DDIRECT
4.2111*
0.0339
20.5929**
0.4076
2.0233
0.0033
DNONMORT
DOASSET
‘Significant at the 5 percent level.
“ Significant at the 1 percent level.
FRB CHICAGO Working Paper
December 1989, WP-1989-24
31
T able 9
Seem ingly unrelated regression results of the response of S& L stock
returns to changes in asse t com ponents1
Alternative decomposition of mortgage portfolio
High* and low-risk S& Ls
Equation
High-risk S&Ls
Low-risk S&Ls
-0.0082
(5.853)***
-0.0029
(4.174)***
1.6270
(11.029)***
1.0797
(14.426)***
RTBOND
0.4046
(2.238)**
0.5566
(6.040)***
LIBGROW
-0.0136
(0.677)
0.0004
(0.324)
DRMORT
-0.0001
(0.198)
0.0002
(0.590)
DCMORT
0.0018
(4.395)***
0.0003
(0.408)
DADL
0.0022
(2.870)***
-0.0037
(2.974)***
DOMORT
0.0005
(1.528)
-0.0002
(0.571)
DDIRECT
0.0021
(2.447)**
-0.0003
(0.219)
DNONMORT
0.0044
(4.488)***
-0.0002
(0.261)
DOASSET
0.0008
(3.059)***
0.00002
(0.008)
CONSTANT
RMKT
R2
0.3581
21.255
F
The weighted R-square for the system = 0.4148
0.4361
29.068
1Numbers in parentheses below the regression coefficients are the absolute value of the
corresponding t-ratios.
2Rounded to zero.
“ Significant at the 5 percent level.
‘“ Significant at the 1 percent level.
FRB CHICAGO Working Paper
December 1989, WP-1989-24
32
T able 10
T ests for the equality of asset coefficients
with that on DRMORT (F-statistics)
Using Table 10 coefficients
Variable
DCMORT
High-risk S&Ls
15.9873**
Low-risk S&Ls
0.0088
DADL
7.2534**
9.6680**
DDIRECT
5.7018*
0.1657
21.0550**
0.3027
5.2576*
0.2849
DNONMORT
DOASSET
‘Significant at the 5 percent level.
••Significant at the 1 percent level.
FRB CHICAGO Working Paper
December 1989, WP-1989-24
33
Federal Reserve Bank o f Chicago
R E S E A R C H S T A F F M E M O R A N D A , W O R K I N G P A P E R S A N D S T A F F S T U D IE S
The following lists papers developed in recent years by the Bank’ s research staff. Copies o f those
materials that are currently available can be obtained by contacting the Public Inform ation Center
(312) 322-5111.
Working Paper Series—A series o f research studies on regional economic issues relating to the Sev
enth Federal Reserve District, and on financial and economic topics.
Regional Economic Issues
D onn a Craig Vandenbrink
“ The Effects o f Usury Ceilings:
the Econom ic Evidence,” 1982
David R . Allardice
“ Small Issue Industrial Revenue Bond
Financing in the Seventh Federal
Reserve District,” 1982
W P -83-1
W illiam A . Testa
“ Natural G as Policy and the M idwest
R egion,” 1983
W P -86-1
Diane F. Siegel
W illiam A . Testa
“ Taxation o f Public Utilities Sales:
State Practices and the Illinois Experience”
W P -87-1
A lenka S. Giese
W illiam A . Testa
“ Measuring Regional H igh Tech
Activity with Occupational D a ta ”
W P -8 7 -2
Robert H . Schnorbus
Philip R. Israilevich
“ Alternative Approaches to Analysis o f
Total Factor Productivity at the
Plant Level”
W P -8 7 -3
A lenka S. Giese
W illiam A . Testa
“ Industrial R & D A n Analysis o f the
Chicago A rea”
W P -8 9 -1
W illiam A . Testa
“ M etro Area G row th from 1976 to 1985:
Theory and Evidence”
W P -8 9 -2
W illiam A . Testa
Natalie A . Davila
“ Unem ploym ent Insurance: A State
Econom ic Developm ent Perspective”
W P -8 9 -3
Alenka S. Giese
“ A W indow o f Opportunity Opens for
Regional Econom ic Analysis: B E A Release
Gross State Product D a ta ”
W P -8 9 -4
Philip R . Israilevich
W illiam A . Testa
“ Determining Manufacturing Output
for States and Regions”
W P -8 9 -5
Alenka S.Geise
“ The Opening o f M idw est Manufacturing
to Foreign Com panies: The Influx o f
Foreign Direct Investment”
W P -8 9 -6
Alenka S. Giese
Robert H . Schnorbus
“ A N ew A pproach to Regional Capital Stock
Estimation: Measurement and
Performance”
* W P -8 2 -l
* *W P -8 2 -2
*Limited quantity available.
**Out of print.
Working Paper Series (cont'd)
W P -8 9 -7
W illiam A . Testa
“ W h y has Illinois M anufacturing Fallen
Behind the Region?”
W P -8 9 -8
Alenka S. Giese
W illiam A . Testa
“ Regional Specialization and Technology
in M anufacturing”
W P -8 9 -9
Christopher Erceg
Philip R. Israilevich
Robert H . Schnorbus
“ Theory and Evidence o f Tw o Competitive
Price Mechanism s for Steel”
W P -8 9 -1 0
D avid R. Allardice
W illiam A . Testa
“ Regional Energy Costs and Business
Siting Decisions: A n Illinois Perspective”
W P -89-21
W illiam A . Testa
“ M anufacturing’ s Changeover to Services
in the Great Lakes E conom y”
W P -90-1
P .R . Israilevich
“ Construction o f Input-Output Coefficients
with Flexible Functional Form s”
Issues in Financial Regulation
W P -89-11
D ouglas D . E va n off
Philip R. Israilevich
Randall C . Merris
“ Technical Change, Regulation, and Econom ies
o f Scale for Large Com mercial Banks:
A n Application o f a M odified Version
o f Shepard’ s Lem m a”
W P -8 9 -1 2
D ouglas D . E van off
“ Reserve Account M anagem ent Behavior:
Impact o f the Reserve Accounting Scheme
and Carry Forward Provision”
W P -8 9 -1 4
G eorge G . K aufm an
“ A re Some Banks too Large to Fail?
M y th and Reality”
W P -8 9 -1 6
R am on P. D e Gennaro
James T . M oser
“ Variability and Stationarity o f Term
Premia”
W P -8 9 -1 7
Thom as M ondschean
“ A M odel o f Borrowing and Lending
with Fixed and Variable Interest Rates”
W P -8 9 -1 8
Charles W . Calomiris
“ D o "Vulnerable" Econom ies Need Deposit
Insurance?: Lessons from the U .S .
Agricultural B oom and Bust o f the 1920s”
W P -8 9 -2 3
G eorge G . K au fm an
“ The Savings and Loan Rescue o f 1989:
Causes and Perspective”
W P -8 9 -2 4
Elijah Brewer III
“ The Impact o f Deposit Insurance on S& L
Shareholders’ Risk/Return Trade-offs”
♦Limited quantity available.
♦♦Out of print.
Working Paper Series (cont'd)
Macro Economic Issues
W P -8 9 -1 3
David A . Aschauer
“ Back o f the G -7 Pack: Public Investment and
Productivity G row th in the G roup o f Seven”
W P -8 9 -1 5
Kenneth N . Kuttner
“ M onetary and N o n -M o n etary Sources
o f Inflation: A n Error Correction Analysis”
W P -8 9 -1 9
Ellen R. Rissman
“ Trade Policy and U n io n -W ag e D ynam ics”
W P -8 9 -2 0
Bruce C . Petersen
W illiam A . Strauss
“ Investment Cyclicality in Manufacturing
Industries”
W P -8 9 -2 2
Prakash Loungani
Richard Rogerson
Y a n g -H o o n Sonn
“ Labor M obility, Unem ploym ent and
Sectoral Shifts: Evidence from
M icro D a ta ”
♦Limited quantity available.
**Out of print.
4
Staff Memoranda— A
series o f research papers in draft form prepared by members o f the Research
Department and distributed to the academic comm unity for review and comm ent. (Series discon
tinued in December, 1988. Later works appear in working paper series).
* * S M -8 1 -2
George G . K au fm an
“ Impact o f Deregulation on the M ortgage
M ark et,” 1981
** S M -8 1 -3
A lan K . Reichert
“ A n Examination o f the Conceptual Issues
Involved in Developing Credit Scoring M odels
in the Consumer Lending Field,” 1981
Robert D . Laurent
“ A Critique o f the Federal Reserve’ s N ew
Operating Procedure,” 1981
George G . K au fm an
“ Banking as a Line o f Com m erce: The Changing
Competitive Environm ent,” 1981
S M -82-1
Harvey Rosenblum
“ Deposit Strategies o f M inim izing the Interest
Rate Risk Exposure o f S & L s,” 1982
* S M -8 2 -2
George K au fm an
Larry M o te
Harvey Rosenblum
“ Implications o f Deregulation for Product
Lines and Geographical M arkets o f Financial
Instititions,” 1982
♦ S M -82-3
George G . K aufm an
“ The Fed’ s Post-October 1979 Technical
Operating Procedures: Reduced Ability
to Control M o n e y ,” 1982
S M -8 3 -1
John J. D i Clemente
“ The Meeting o f Passion and Intellect:
A History o f the term ‘ Bank’ in the
Bank H olding C om pany A c t ,” 1983
S M -8 3 -2
Robert D . Laurent
“ Com paring Alternative Replacements for
Lagged Reserves: W h y Settle for a Poor
Third Best?” 1983
G . O. Bierwag
George G . K au fm an
“ A Proposal for Federal Deposit Insurance
with Risk Sensitive Premiums,” 1983
Henry N . Goldstein
Stephen E. Haynes
“ A Critical Appraisal o f M c K in n o n ’ s
W o rld M on ey Supply H ypothesis,” 1983
S M -8 3 -5
George K au fm an
Larry M o te
Harvey Rosenblum
“ The Future o f Com mercial Banks in the
Financial Services Industry,” 1983
S M -8 3 -6
V efa Tarhan
“ Bank Reserve Adjustm ent Process and the
Use o f Reserve Carryover Provision and
the Implications o f the Proposed
Accounting R egim e,” 1983
S M -8 3 -7
John J. D i Clemente
“ The Inclusion o f Thrifts in Bank
Merger Analysis,” 1983
S M -8 4 -1
Harvey Rosenblum
Christine Pavel
“ Financial Services in Transition: The
Effects o f N onbank C om petitors,” 1984
S M -8 1 -4
** S M -8 1 -5
* * S M -8 3 -3
* S M -8 3 -4
^Limited quantity available.
**Out of print.
Staff Memoranda (cont'd)
S M -8 4 -2
George G . K aufm an
“ The Securities Activities o f Com mercial
Banks,” 1984
S M -8 4 -3
G eorge G . K au fm an
Larry M o te
Harvey Rosenblum
“ Consequences o f Deregulation for
Com mercial Banking”
S M -8 4 -4
G eorge G . K aufm an
“ The Role o f Traditional M ortgage Lenders
in Future M ortgage Lending: Problems
and Prospects”
S M -8 4 -5
Robert D . Laurent
“ The Problems o f M onetary C ontrol Under
Quasi-Contem poraneous Reserves”
S M -8 5 -1
Harvey Rosenblum
M . Kathleen O ’ Brien
John J. D i Clemente
“ O n Banks, N onbanks, and Overlapping
M arkets: A Reassessment o f Com mercial
Banking as a Line o f C om m erce”
S M -8 5 -2
T h om as G . Fischer
W illiam H . G ram
George G . K aufm an
Larry R . M o te
“ The Securities Activities o f Com m ercial
Banks: A Legal and Econom ic Analysis”
S M -8 5 -3
George G . K aufm an
“ Implications o f Large Bank Problems and
Insolvencies for the Banking System and
Econom ic Policy”
S M -8 5 -4
Elijah Brewer, III
“ The Impact o f Deregulation on The True
C ost o f Savings Deposits: Evidence
From Illinois and W isconsin Savings &
Loan A ssociation”
S M -8 5 -5
Christine Pavel
Harvey Rosenblum
“ Financial Darwinism: N onbanks—
and Banks—Are Surviving”
S M -8 5 -6
G . D . Koppenhaver
“ Variable-Rate Loan Com m itm ents,
Deposit Withdrawal Risk, and
Anticipatory H edging”
S M -8 5 -7
G . D . Koppenhaver
“ A N o te on M anaging Deposit Flows
W ith Cash and Futures M arket
Decisions”
S M -8 5 -8
G . D . Koppenhaver
“ Regulating Financial Intermediary
Use o f Futures and Option Contracts:
Policies and Issues”
S M -8 5 -9
D ouglas D . E va n off
“ The Impact o f Branch Banking
on Service Accessibility”
S M -8 6 -1
George J. Benston
G eorge G . K au fm an
“ Risks and Failures in Banking:
Overview, History, and Evaluation”
S M -8 6 -2
D avid A lan Aschauer
“ The Equilibrium A pproach to Fiscal
Policy”
*Limited quantity available.
**Out of print.
@FedFRASER