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SEPTEMBER/OCTOBER 19 9 3
ECONOMIC PERSPECTIVES
Contents
Tracking Midwest manufacturing
and productivity growth..............................................................................2
P h ilip R. Is ra ile vich , K enn eth N. K u ttn e r,
and R obert H. Schnorbus
During the 1980s, Midwest manufacturing experienced a
“productivity takeoff.” The authors explore the scope and
causes of that takeoff as well as its implications for the
mixed-frequency Midwest Manufacturing Index.
Why the life insurance industry
did not face an "S&L-type" crisis............................................................... 12
Elijah B rew er III, T ho m as H. M o nd schean ,
and Ph ilip E. S trah an
Declines in real estate values and junk bond prices in the
late 1980s adversely affected both life insurance
companies and savings and loan associations. Yet
important differences between the two industries,
especially in the way they are regulated, prevented a
crisis from occurring in the life insurance industry.
R <( )i\( )\11( i PER SPL( j1 IV ES
i(
Sep tem ber/O ctob er 1993 V o lum e X V II, Issue 5
Karl A. Scheld, Senior Vice President and
Director o f Research
ECONOMIC PERSPECTIVES is published by
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Janice W eiss, editor
David R. Allardice, regional studies
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Anne Weaver, administration
Production
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Kathryn Moran, assistant editor
ISSN 0164-0682
Tracking Midwest manufacturing
and productivity growth
P h ilip R. Israilevich , Kenneth N. K u ttn er,
and R obert H. Schnorbus
higher in the region than in the rest of the nation.
After years of lagging econom
We then use the mixed-frequency MMI to assess
ic performance that led to the
region’s characterization as a
the quantitative significance of the increased
“rust belt,” Midwest manufac
productivity growth for current estimates of
turers have exhibited increas
Midwest output.
ing competitiveness in the last several years, The productivity takeoff identified in this
compared with the rest of the nation andanalysis has important implications for the MMI
with
model, which relies on historical rates of produc
their own earlier performance.* Evidence of this
tivity growth to account for the divergence of
strong performance is the fact that the Midwest’s
output and
output grew faster on average than the nation’s, employment data, and to compute
current
given observed rates of capital and labor usage. estimates of the index. In light of the
evidence, we reconsider the assumption of a
A common explanation for this resurgence
constant rate of productivity growth for each
has been that in the 1980s, Midwest manufactur
industry, and suggest a modification to the MMI
ers undertook aggressive modernization pro
grams in an attempt to reverse their fortunes.
model that will allow it to capture the technical
This explanation, however, rests largely on
progress that resulted from modernization of
core Midwest industries.
anecdotal evidence; data have been hard to come
by. With the help of annual production models,
Investm ent and th e p ro d u c tiv ity ta k e o ff
the mixed-frequency Midwest Manufacturing
in th e M id w e s t
Index (MMI) developed by Israilevich and Kutt
The key to regional growth is improving
ner (1993), and annual capital expenditure data
competitiveness, and the key to increasing a
from the U.S. Commerce Department, we are
region’s competitiveness is productivity growth
beginning to reach a clearer understanding of the
relative to other regions. Such productivity
region’s improvements in productivity and com
gains can be achieved in at least two ways: fast
petitiveness as Midwest manufacturers move
er withdrawal of the least productive capital
into the 1990s.
stock (downsizing) than elsewhere, and faster
In this article, we explore the reasons for the
introduction of new, more technologically ad
so-called takeoff in Midwest manufacturing
vanced plant and equipment than elsewhere.
productivity, tracing its growth to significant
While both measures can yield increased output
modernization efforts in several key industries.
per worker, they have different implications for
Investment data and estimates of production
models both suggest that productivity gains were
■
*The Midwest is defined here to include the five states in
the Seventh Federal Reserve District: Illinois, Indiana,
Iowa, Michigan, and Wisconsin.
Philip R. Israilevich is Senior Economist, Kenneth
N. Kuttner is Senior Research Economist and
Research Officer, and Robert H. Schnorbus is
Senior Business Economist and Research Officer,
all at the Federal Reserve Bank of Chicago.
2
ECONOMIC PERSPECTIVES
future growth. If the recent produc
FIGURE 1
tivity gains in the Midwest were
Capital expenditures per worker
achieved only by shrinking the man
thousands of current dollars per worker
ufacturing base without moderniz
ing, the region would be vulnerable
to further declines as other regions
improve their competitiveness and
increase their market share at the
Midwest’s expense. However, if
Midwest manufacturers were mod
ernizing while they were closing
antiquated facilities, they might
offset any net reductions in capital
stock with productivity gains suffi
cient to allow output growth relative
to the rest of the nation.
In the early 1980s, manufactur
Source: U.S. Department of Commerce, Bureau of the Census, Survey of
ers were under severe financial
Manufacturers and Census of Manufacturers, various issues.
stress, particularly in the Midwest.
A relatively deep recession in
1980-82 was followed by an intensification of
worker in the Midwest and in the rest of nation
global competition caused in part by a strong
does not appear to be due to differences in in
dollar. Many well-known companies such as
dustrial mix. Indeed, both the auto and steel
Caterpillar, USG, and Chrysler were pushed
industries show higher investment per worker in
the region than in the rest of the nation. For
dangerously close to bankruptcy; virtually all
manufacturers in the Midwest scrambled to cut
example, between 1986 and 1990, investment
costs in order to be as competitive as possible in
per worker in the transportation industry was 16
an increasingly tough global market. As part of
percent higher on average in the Midwest than in
that effort, many old or marginally profitable
the rest of the nation; in primary metals it was 22
plants were closed under the banner of
percent higher on average. While these two
“rationalization”—a term which in the 1990s
industries show larger differentials than other
would be dubbed “re-engineering.”
industries, they demonstrate that the pattern
Despite these financial problems, many
observed at the aggregate manufacturing level
Midwest manufacturers met the increasing com
reflects a widespread commitment to moderniza
petitive pressures of the early 1980s with aggres
tion among Midwest manufacturers.
sive capital spending programs. While with
A closer look at the auto and steel industries
drawing older capital stock, they also invested in
reveals the dual nature of the adjustments that
new plants and equipment. The only question
manufacturers made in response to competitive
was whether these adjustments were occurring at
problems. During the 1980s, automakers closed
a faster pace in the region than they were else
seventeen car and truck assembly plants, of
where in the nation.
which six were in the Midwest. At the same
Before 1985, the Midwest tended to invest
time, they constructed seventeen plants, seven of
at roughly the same rate as the rest of the nation.
them in the Midwest. Some of the new plants
Investment in the region picked up in the late
were essentially replacements of existing Big
1970s but slowed again with the onset of the
Three plants, for example, Chrysler’s Jefferson
1980-82 recession. Thereafter, Midwest invest
Avenue plant in Detroit. But some were entirely
ment lagged the rest of the nation until a push
new plants built by foreign auto companies,
resumed in 1985.1 As figure 1 shows, between
often in conjunction with a Big Three producer.
1986 and 1990, average capital expenditure per
Among the foreign-owned plants are the Dia
worker in the Midwest was 9 percent above the
mond Star Plant in Illinois (Chrysler and Mit
amount for the rest of the nation.
subishi) and the Flat Rock Plant in Michigan
The Midwest contains a high proportion of
(Ford and Mazda).
capital-intensive industries, notably auto and
A somewhat similar pattern of investment
steel, yet the difference between investment per
occurred in the Midwest steel industry, where
FEDERAL RESERVE
BANK OF CHICAGO
3
integrated mills were closed and the remaining
mills modernized. Inland Steel, for example, has
invested roughly $1 billion since 1985 to mod
ernize its Indiana Harbor Works in East Chica
go, Indiana (which included converting to con
tinuous casting). The company spent another $1
billion on a new mill in Indiana, a joint venture
with a Japanese producer. While integrated steel
producers were modernizing, they were also
opening mini-mills that brought a wholly differ
ent production process to U.S. steelmaking.
The result was that both the auto and steel
industries saw more productivity gains in the
Midwest than in the rest of the nation. These
gains made Midwest producers more competi
tive and allowed industry in the region to grow
faster than elsewhere.
capital inputs), 0 and < are the elasticities of
\>
output with respect to labor and capital, and r\
is a random error term. The Cobb-Douglas
specification is also consistent with the mixedfrequency MMI introduced subsequently, as
well as a variety of other indices discussed in
Israilevich et al. (1989).
We first estimated the production function
over the sample running from 1973 through
1985, dates chosen on the basis of the Midwest
investment patterns discussed above. Using this
estimated function, we then projected output for
the 1986-90 period on the basis of pre-1986
“old” technology, and compared the projection
to the actual VA data, the result of production
with “new” technology.
P ro d u c tiv ity g ro w th in th e M id w e st:
e v id e n ce fro m ann ual data
Table 1 reports the difference between
projected and observed output growth for 15 key
manufacturing industries in the Midwest, aggre
gated into five sectors: transportation, metal
working, machinery, chemicals, and consumer
products. Table 2 shows the composition of
these sectors and a breakdown of Midwest out
put by industry. For comparison purposes, simi
lar calculations were done for the rest of the
nation. According to these estimates, between
1986 and 1990, Midwest manufacturing sectors
improved efficiency by 8 percent more than the
corresponding sectors in the rest of the nation.
Given the capital-intensive nature of most Mid
west industries and their relative maturity, such a
gain is substantial. It would also help explain
why output has been growing faster in the region
than in the nation since the late 1980s.
Figure 2 displays the efficiency gains graph
ically, showing the Midwest’s lead as a function
of time. While the gap between observed and
The investment patterns noted above sug
gest that Midwest manufacturers began to mod
ernize aggressively around 1986. What is lack
ing is some measure of how much efficiency
increased as a result. How much has Midwest
manufacturing output grown, compared with the
growth that would have occurred using pre-1986
technology?
One way to address this question is simply
to compare the out-of-sample forecasts from a
production function estimated on data from 1973
through 1985 with observed output from 1986 to
the present. A natural and intuitive measure of
the size of the takeoff is the difference between
the Midwest’s observed output and the model’s
prediction: that is, the amount by which actual
output exceeds what would have been produced
had pre-1986 technology been applied to the
actual factor inputs.
A convenient production function for this
analysis is the Cobb-Douglas specification,
The Midwest versus the nation
TABLE 1
Efficiency gains, 1986-90
(percent)
*,= Y-f + 0/,+ <K+Tl,,
where * represents output of a given industry
measured by the logarithm of real value added
(VA), t indexes the year, l is the logarithm of
payroll employment, and e is the logarithm of
electricity consumption. For applications such
as this, energy consumption is widely interpreted
as a proxy for the utilized stock of capital.2
The y coefficient on the time trend represents
the rate of Hicks-neutral technological change
(i.e., productivity not embodied in either labor or
4
M id w e s t
Rest of
n a t io n
Transportation
7.94
3.83
Metalworking
2.03
2.38
Machinery
2 .0 1
0.89
S e c to r
Chemicals
Consumer products
T o ta l
ECONOMIC PERSPECTIVES
0.76
3.10
-3.33
-0.58
1 .3 8
1 .2 8
TABLE 2
Composition of Midwest manufacturing output, 1990
Sector
Share (%)
Industry
Share (%)
Transportation
14
Transportation (SIC 37)
14
M etalw orking
14
Primary metals (SIC 33)
5
Fabricated metals (SIC 34)
8
M achinery
15
Nonelectrical (SIC 35)
26
Electrical (SIC 36 and 38)
Chemicals
36
10
Chemicals (SIC 28)
8
Petroleum (SIC 29)
22
5
Clay, glass and stone (SIC 32)
Consumer products
1
Rubber and plastic (SIC 30)
1
Food (20)
Lumber and w ood (SIC 24)
11
1
Furniture and fixtures (SIC 25)
2
Paper products (SIC 26)
Printing and publishing (SIC 27)
3
4
Miscellaneous (SIC 39)
1
Note: Industry subtotals may not equal sector totals because of rounding.
predicted output remained positive, it flattened
out in 1989 and declined in 1990. Only in 1990
did the rate of improvement in efficiency seem
to subside, both in the Midwest and elsewhere.
This pattern suggests that the shift in the national
economy from a mini-boom in 1988-89 (rough
ly 4 percent real GDP growth) to virtual stagna
tion (roughly 1-2 percent real GDP growth) had
an impact on efficiency gains. Perhaps the cy
clical drop in output growth prior to the 1990-91
recession led to underutilization of labor and
capital, which reduced the measure of efficiency
gains over the second half of the 1980s. More
over, the commitment to efficiency gains even in
a sluggish economy may help explain why man
ufacturers have been able to expand output since
the 1990-91 recession even though employment
growth has been virtually nonexistent.
in the region’s core manufacturing sectors, trans
portation and machinery.
The Midwest’s transportation sector scored
the most impressive gains in efficiency. Output
in this sector was 7.9 percent higher than fore
cast on the basis of pre-1986 technology, com
pared to 3.8 percent higher in the rest of the
Comparisons between Midwest industries
The efficiency gains identified in table 1
were clearly not uniform across the Midwest’s
industries. How widespread were they, and how
much of the total gain was due to the industrial
structure of the region relative to the rest of the
nation? The gains did seem to be concentrated
FEDERAL RESERVE
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5
nation. In the Midwest, the transportation sector
is dominated by automobile manufacturers and
parts suppliers, both of which were troubled
industries throughout the 1980s. Japanese im
ports and nameplates produced in the U.S. had
been gaining market share for many years, leav
ing the domestic industry with tremendous over
capacity. The first wave of restructuring took
place in the early 1980s when Ford and Chrysler
began closing plants. GM began closing assem
bly plants in the late 1980s and is currently in a
second wave of closings that will extend into
1995. At the same time that Big Three automak
ers were closing plants, both they and the Japa
nese were opening state-of-the-art assembly
plants in the Midwest as well as elsewhere.
Over the 1980s, the region’s share of total car
production actually rose from 39 to 44 percent,
although its share of truck production declined
from 40 to 28 percent.
The Midwest’s machinery sector also out
paced the rest of the nation. While in the rest of
the nation machinery was on average 0.9 percent
above its predicted level of output over the
1986-90 period, in the Midwest it was 2 percent
higher than predicted on the basis of the pre1986 technology. The region’s machinery sector
is largely focused on the auto industry and ex
ports. As suppliers of the new capital, this sector
has been in the forefront of the recent wave of
investment targeted to meet global competition.
Machinery producers themselves have faced stiff
competition from foreign competitors, particu
larly the Japanese. Moreover, some machinery
producers have been bought out by foreign com
panies, a change that often brings an infusion of
fresh capital that improves productivity. It is
encouraging to see that machinery producers,
especially in the Midwest, have accepted the
challenge of heightened global competition by
increasing capital expenditures rather than by
closing or shifting to other markets.
In the aggregate, the Midwest’s metalwork
ing sector displayed efficiency gains roughly in
line with the rest of the nation. However, disag
gregating the sector into its two constituent
industries, fabricated metals and primary metals
(the steel industry in the Midwest) reveals an
interesting contrast. While the pace of technical
change lagged the nation in fabricated metals,
productivity growth in primary metals exceeded
the nation’s—a divergence that also appears in
the MMI results presented later in this article.
Interestingly, the major downsizing in the steel
6
industry was over by the mid-1980s, leaving the
Midwest as the dominant integrated steel-pro
ducing region. Midwest firms continued invest
ing in modernization, and even mini-mills were
expanding in the region. It is the Midwest’s
continued modernization, and perhaps its domi
nance in the high-quality steel produced by
integrated mills, that allowed the region to out
pace the rest of the nation in productivity. In
contrast to primary metals, the metal fabrication
industry, which produces finished parts from
raw steel, never experienced any significant
consolidation. The small size of producers in
this fragmented industry may have limited the
adoption of technical advances.
While efficiency gains were clearly wide
spread in the Midwest, not all the region’s indus
tries outpaced their counterparts elsewhere in the
nation. The Midwest’s chemical and consumer
products sectors actually lagged the rest of the
nation in efficiency gains over the 1986-90
period. In fact, efficiency in the latter sector was
lower during the period than in previous years.
While these industries are important to the Mid
west, it is interesting that they are generally
outside the auto-steel-machinery complex that
comprises the heart of the region’s manufactur
ing. It is perhaps unfortunate that strength in
this “heart” seems not to spill over into other
industries, yet by the same token, it seems that
weakness in some sectors does not retard effi
ciency gains in other sectors.
T h e p ro d u c tiv ity ta k e o ff and th e MMI
The preceding section discussed measuring
Midwest productivity gains by comparing annu
al V A data with predictions from estimated
production models. An alternative method is to
apply a similar analysis to predictions generated
by the mixed-frequency MMI, as described in
the appendix. The main advantage of the mixedfrequency MMI is that it tracks actual VA more
precisely than other purely annual indices, such
as the annual Cobb-Douglas or Atlanta methods,
when projected out of sample.3 Hence, the MMI
should yield a more accurate assessment of
Midwest efficiency gains than the annual model.
A second reason to use the MMI in this
context is to examine any implications the hy
pothesized productivity takeoff might have for
current estimates of Midwest output. Although
the production model underlying the mixedfrequency MMI is re-estimated as new annual
VA data become available, an increase in the
ECONOMIC PERSPECTIVES
rate of technical progress may require structural
modifications to the model to enable it to track
manufacturing output more accurately in the
future.
Out-of-sample comparisons
To construct a quantitative measure of Mid
west efficiency growth, we first estimated the
mixed-frequency MMI using annual data from
1973 through 1985. We then used monthly
energy, labor, and nationwide Industrial Produc
tion (IP) data to project the MMI forward over
the 1986-90 period, in which annual real VA
data for the Midwest are available. Comparing
the projected series with the actual VA data
yields an index of efficiency gains that is compa
rable to the measures reported earlier. As be
fore, an increase in the rate of productivity
growth would imply that the projected MMI
would underpredict output growth. This short
fall, therefore, represents the region’s gains
expressed in terms of the additional output pro
duced as a result of increased manufacturing
productivity.
Table 3 reports these gains, classified by
industries and sectors. The results are expressed
as the average percentage deviation between
observed real VA growth and the annualized
growth rate of the projected MMI. In metal
working, for example, the reported 0.6 percent
figure signifies that on average, the MMI under
predicted VA growth by 0.6 percent for each
year in the 1986-90 period.
The results are broadly similar to those
based on the annual estimates reported above.
Most striking is the spectacular productivity
growth in the transportation sector, which con
sists entirely of SIC 37. Here, annual productiv
ity growth over 1986-90 was roughly 9 percent
higher than in the preceding 13 years. To restate
this in cumulative terms, by the end of 1990,
output in the transportation sector was about
40 percent higher than it would have been had
firms applied pre-1986 technology to the same
labor and energy factor inputs. Such are the
quantitative effects of the investment flows and
modernization efforts identified earlier.
Although there are a few bright spots, none
of the other sectors showed the kind of spectacu
lar growth detected in transportation. Echoing
the earlier annual results, within metalworking,
primary metals (SIC 33) did well, turning in a
robust average 2.8 percent per year increase in
T A B LE 3
Efficiency gains based on the MMI, 1986-90
S e c to r
G ain (%)
In d u s try
Transportation
9.0
Transportation (SIC 37)
M etalw orking
0 .6
Primary metals (SIC 33)
G a in (%)
9.0
2 .8
Fabricated metals (SIC 34)
M achinery
- 0 .6
- 0 .8
Nonelectrical (SIC 35)
-0.9
Electrical (SIC 36 and 38)
Chemicals
-0.9
0 .2
Chemicals (SIC 28)
-0.3
Petroleum (SIC 29)
-5.7
Rubber and plastic (SIC 30)
0.4
Clay, glass and stone (SIC 32)
Consumer products
FEDERAL RESERVE
-
1 .6
-4.0
Food (SIC 20)
- 0 .1
Lumber and w ood (SIC 24)
5.5
Furniture and fixtures (SIC 25)
Paper products (SIC 26)
- 6 .0
Printing and publishing (SIC 27)
- 0 .6
Miscellaneous (SIC 39)
BANK OF CHICAGO
-3.7
-9.6
7
its rate of productivity growth. The
TABLE 4
slight deterioration in fabricated
Estimated shift in Midwest rate of productivity growth
metals (SIC 34) partly offset this
(annualized percentage)
gain, however, resulting in a modest
1973-85
1986-90
D iffe ren c e
overall gain for metalworking of
only 0.6 percent.
Transportation (SIC 37)
0.1
1 0 .0
9.8*
Neither machinery nor chemi
4.1
3.7
Primary metals (SIC 33)
0.4
cals displayed any significant evi
dence of a productivity acceleration.
* significant at the .05 level.
The small improvement in machin
ery sector productivity evident in the
to the 1973-85 period. If this more rapid
annual results is not apparent in the MMI. The
growth were extrapolated into 1993, then with
rates of technical change in both nonelectrical
the same inputs, output (measured by VA)
(SIC 35) and electrical machinery (SICs 36 and
would be roughly 70 percent higher than it
38) remained close to pre-1986 levels. The rate
would have been using 1973-85 technology.
of technical change also appeared stable in the
The results for primary metals also provide
chemical sector, with chemicals (SIC 28) and
some evidence for a higher productivity growth
rubber and plastic (SIC 30) indices tracking VA
rate, although the statistical significance is weak
quite closely. The exceptions were petroleum
er. While the estimated shift coefficient implies
(SIC 29) and clay, glass and stone (SIC 32),
an increase in annual productivity growth of
whose performance appeared to deteriorate sig
4 percent, it is not statistically significant at the
nificantly. However, given the poor quality of
traditional .05 level.
the data and the very small size of these indus
tries in the Midwest (each only about 1 percent of
Extending the MMI
1990 VA), little weight should be given to these
These findings have potentially important
results.
implications for current appraisals of Midwest
Performance within the consumer products
output. One of the purposes of the MMI is to
sector was rather disappointing overall. All indus
assess the level of manufacturing activity prior
tries showed some diminution in their rate of
to the release of VA data, which become avail
technical change, with the exception of lumber
able after a two- to three-year lag. Contempora
and wood (SIC 24). Since that industry currently
neous estimates of the growth of industry output
accounts for only 1 percent of the Midwest’s
incorporate a weighted average of energy and
output, its impact on the region is small.
labor inputs, plus the rate of productivity growth
relevant for that industry. Updates of the MMI,
Modeling the productivity takeoff
therefore, depend critically on whether this rate
How important are these results statistically?
of productivity growth is stable. Projections that
How might the mixed-frequency MMI model be
did not take into account any productivity accel
extended to allow a changing rate of productivity
eration might as a result seriously understate
growth? What is the impact of more rapid techni
current output levels.
cal change on current estimates of the MMI? To
To assess the consequences on the MMI, we
address these three issues, we re-estimate the
perform one final exercise, comparing post-1990
MMI for the transportation and primary metals
MMI projections with and without a shift in
industries—the two industries that show signifi
productivity growth in 1986. Rather than
cant acceleration in the region—allowing a shift
re-estimate the model for every industry, we
in the productivity growth rate in 1986. The
again concentrate on the two showing some
significance of this shift can then be evaluated
evidence of a productivity takeoff: primary
statistically.
metals (SIC 33) and transportation (SIC 37).
The results of this exercise, as reported in
The results appear in figure 3.
table 4, generally support the out-of-sample
The top panel shows the impact of this
findings. Again, the evidence for a productivity
change on the aggregate MMI. The effect is
takeoff is strongest for transportation, which
small but perceptible. The cumulative discrep
experienced a statistically significant increase in
ancy relative to the unadjusted index was
annual productivity growth of 10 percent relative
8
ECONOMIC PERSPECTIVES
These results demonstrate that
if the productivity acceleration had
continued from 1990 to the present,
it may have had a noticeable impact
on the MMI; accordingly, the exist
ing MMI would have understated
the Midwest’s actual output from
1991 to 1993. Should the index then
be modified to incorporate higher
rates of productivity growth in cer
tain industries? Clearly, the answer
depends on recent productivity
developments. For example, if we
assumed that the 1986-90 rate of
change had continued into 1993 but
it had actually levelled off, then
modifying the MMI would intro
duce an upward bias into it. For
this reason, the appropriate incorpo
ration of changes to the MMI model
requires an ongoing, disaggregated
examination of the structure of the
economy.
C o n c lu s io n
2 percent as of April 1993. Naturally, the effects
on the individual industries, depicted in the
middle and bottom panels, are larger. As ex
pected in light of the earlier results, the most
pronounced effect is in transportation, where the
adjusted MMI is 15 percent higher than the
unadjusted by April 1993. The cumulative im
pact on primary metals is a smaller but still
substantial 3 percent.
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Despite falling levels of em
ployment, Midwest manufacturing
output expanded rapidly during the
1980s. This growth, which sur
passed national output growth over
the period, suggests improved com
petitiveness among the region’s
manufacturers. The evidence con
firms this impression. Comparing
the predictions of production mod
els applied to annual Midwest data
with similar predictions for the rest
of the nation showed that the re
gion’s brisk expansion was due in
large part to strong productivity
growth. The main cause of this
growth appears to have been the
aggressive modernization efforts of
Midwest manufacturers, as reflected
in the region’s higher rate of investment per
worker relative to the national average.
Using the MMI to evaluate the size and scope
of the productivity gains, we found that they were
largely confined to a few key industries, particu
larly transportation and primary metals. Howev
er, given the prominence of these industries in the
Midwest, their impact on overall manufacturing
output is substantial, possibly raising current
9
estimates in excess of 2 percent if the productivi
ty growth observed from 1986 through 1990
continued into 1993. This finding underlines the
importance of incorporating higher rates of
technical change for certain industries into future
updates of the MMI to reflect the continuing
modernization of Midwest manufacturing.
APPENDIX
T ra c k in g M id w e s t m a n u fa c tu rin g w ith th e
m ixe d -freq u e n cy M M I
A useful tool for analyzing Midwest manufactur
ing is the mixed-frequency Midwest Manufacturing
Index (MMI) developed by Israilevich and
Kuttner (1993). While this technique uses the CobbDouglas production function employed in the annual
results, it differs from this specification in its use of a
monthly production model. At the same time, it
constrains the estimated monthly production series in
such a way as to be consistent with the observed
annual value added (VA) data; hence the “mixedfrequency” designation.
Incorporating monthly data yields two signifi
cant advantages over annual models. First, it makes
it possible to track high-frequency fluctuations in
Midwest output. Second, the mixed-frequency MMI
has been shown to provide more accurate out-ofsample projections of manufacturing activity than
pure annual models. Since annual VA data are not
yet available for the Midwest, this benefit is particu
larly useful for assessing the effects of accelerated
technical change on the current output of the region’s
manufacturing sector.
The foundation of the mixed-frequency MMI is
a Cobb-Douglas production equation applied to
monthly data. Expressed as first differences of natu
ral logarithms, the monthly change in the real output
of any Midwest industry, Ax7s, is the weighted sum
t
of the change in employment hours, Al7 and energy
ts,
usage, Ae^:
Axls = y+QAll + ^Aels+ i\ts.
As in the annual model, y is the (constant) rate of
Hicks-Neutral technical change, 0 and < represent the
|>
elasticity of output with respect to labor and capital
(energy), and T is a stochastic error term. The super
)
script 7 is used to denote Midwest data. Note that
with the shift to monthly data, each variable now
receives two subscripts. The first, t, denotes the year,
while the second, s, represents the month within that
year. Thus the change in output between the second
and third months of the 13th year of the sample would
be denoted Ax7 3.
I3
A difficulty with this approach is that while
monthly energy and labor data are available for the
Midwest, no monthly output measure exists. The
only available measure of region’s production is the
10
real value added (VA) data used in the annual results.
In light of this data limitation, estimating the monthly
model might appear to be a lost cause, since tradi
tional regression techniques require the observations
on the left-hand variable to be available at the same
frequency as those for the right-hand variables.
Using regression methods, therefore, requires that
energy and labor be aggregated to an annual frequen
cy. This is the approach used earlier to compare
productivity growth in the Midwest and in the rest of
the nation.
Fortunately, there are ways around this obstacle.
Techniques exist to combine data of differing fre
quencies into a single model. For the mixed-frequen
cy MMI, we use a state-space econometric model
that treats Midwest output growth as a latent vari
able. Given some additional relationships between
the unobserved Ax7 and other data series, the month
s
ly model can be estimated even in the absence of
direct information on Midwest output.
One key link between Ax7 and something
s
observable is the “adding up” relationship between
the monthly growth of output and the annual growth
of the real VA data. Because the annual VA obser
vations correspond to the sum of the output produced
in each month, the year-to-year change in real VA is
actually a weighted average of the monthly output
growth in the current and preceding 23 months.
Thus, constraining the monthly growth rates to pro
duce an annual pattern consistent with the VA data
implies that
In(VAj) - In(VAj j) = -±- • I
E Ax1 .,
Imposing this equation enforces consistency
between the estimated MMI and the annual VA
data.This relationship alone is not enough for the
monthly approach to yield any dividends, since all
the available information is still coming at an annual
frequency. In order to make inferences about fluctu
ations within the year, we need an additional source
of monthly information. One source of such informa
tion is the monthly index of industrial production (IP)
prepared by the Federal Reserve Board. Besides the
energy and labor inputs used as inputs to the MMI,
the IP typically incorporates some information on
actual output, such as the dollar value or physical
quantity of goods shipped. Thus the IP index con-
ECONOMIC PERSPECTIVES
tains information on industry output not captured by
energy and labor inputs alone. However, the infor
mation in the IP index pertains to the nation, not to
the Midwest. Therefore we cannot simply use IP to
compute Ax7s. Instead, we relate national to regional
t
fluctuations by using an equation to describe the co
movement of the two series:
Mixed-frequency MMI model estimates
for primary metals (SIC 33)
As before, Ax7 represents the growth in Mid
ts
west output; Ax"s is the growth of national output in
the same industry as measured by industrial produc
tion. The coefficient 5 relates the magnitude of the
national fluctuations to those of the region, and v is
random “noise” in the relationship.
Unlike the production model introduced earlier,
this equation does not describe any fundamental
economic or structural relationship between the
region and the nation. Neither is the national IP in
any way a determinant of regional output in the same
way that regional labor and energy inputs are. Rath
er, this equation describes how Midwest economic
fluctuations have historically been paralleled by
movements on a national scale.
Clearly, the fact that Midwest industry compris
es a portion of the national total, implies a positive
correlation between the region and the nation, repre
sented by a positive value of 8. But to the extent that
industries within and outside the region are subject to
similar demand conditions, one might expect the
correlation to be even greater than suggested by the
industry’s share in total output. It is unlikely, how
ever, that 8 would exceed 1, since many regional
fluctuations will be damped by offsetting fluctuations
IP indicator equation
< = 0.33*
f>
p = 0.00
0 = 1. 11 *
Ax"s = •u + SAxl, s + v,, s .
t,
t
t
Production m odel
8
7 = 0.001
Standard deviation
of v = 0.025
Standard deviation
of r| = 0.038
= 0.54*
Note: Based on the 1973-90 sam ple.
* significant at the .01 level.
in the rest of the nation. While the 8 parameter picks
up the relative magnitudes of industrial fluctuations,
the standard deviation of v captures the amount of
“noise,” or unpredictable variation, in the link be
tween regional and national output.
Table 5 shows the results from estimating the
mixed-frequency MMI model for one representative
industry: primary metals (SIC 33). The estimates of
the production function’s parameters all fall within
the range of economically reasonable values, al
though the sum of < and 0 imply increasing returns to
\>
scale. The estimate of y (which is constant through
out the sample) suggests only very modest productiv
ity growth of 1.4 percent per year. The very small
estimate of p. indicates that output has grown at
roughly the same rate in the nation as in the Midwest.
The estimated 8 of 0.54, however, suggests that IP
fluctuations in the nation are approximately half the
magnitude of fluctuations in the Midwest.
FOOTNOTES
'Estimates o f Midwest capital expenditures for the years
1979-81 are not available in the Commerce Department’s
Annual Survey o f Manufacturing (ASM). Values were
calculated by first comparing a sample of 480 Midwest
firms with 100 or more employees, taken from the Longitu
dinal Research Data (LRD) base for the years 1985-88,
with the reported ASM data for those years and, second,
applying the average proportions to the LRD base to gener
ate ASM-equivalent data.
2Moody (1974) discusses the use of energy as a proxy for
capital services.
3A description o f the Atlanta method appears in Israilevich
and Kuttner (1993).
REFERENCES
Israilevich, Philip R., Robert H. Schnorbus, and
Peter R. Schneider, “Reconsidering the regional
manufacturing indexes,” Federal Reserve Bank of
Chicago Economic Perspectives, Vol. 13, No. 4,
July/August 1989, pp. 13-21.
Israilevich, Philip R., and Kenneth N. Kuttner,
“A mixed-frequency model of regional output,”
FEDERAL RESERVE
RANK OF CHICAGO
Journal of Regional Science, Vol. 33, No. 3, forth
coming 1993, pp. 321—
43.
Moody, Carlisle E., “The measurement of capital
services by electrical energy,” Oxford Bulletin of
Economics and Statistics, Vol. 36, No. 1, February
1974, pp. 45-52.
11
Why the life insurance industry
did not face an "S&L-type" crisis
Elijah B rew er III, Thom as H. M ondschean,
and P h ilip E. S trahan
Since August 1989, the Resolu
tion Trust Corporation has
l spent $84.4 billion of taxpayers’ money to close 653 savJSllfiB ings and loan associations
(S&Ls).1 In addition, between 1986 and 1990,
over 900 commercial banks were closed with
assets totaling over $100 billion. On July 16,
1991, in response to policyholder runs during the
previous three months totaling approximately
$500 million, New Jersey regulators seized the
Mutual Benefit Life Insurance Company. The
asset quality problems that led to this and other
runs on life insurance companies in the early
1990s have led some to wonder whether yet
another category of financial intermediaries
might suffer widespread failures requiring gov
ernment intervention at taxpayer expense. Gov
ernment closings of financial institutions can be
extremely costly to taxpayers, and the safety of
life insurance policies and annuity contracts is of
concern to millions of policyholders. For these
reasons alone, it is important to assess the risk
exposure and regulatory structure of the U.S. life
insurance industry.2
But there are other reasons as well. First,
according to the Federal Reserve Flow o f Funds,
the industry held approximately $1.2 trillion in
assets at the end of 1991, accounting for 11.4
percent of total financial assets. Capital adequa
cy or asset quality problems in this industry
could lead to disintermediation, or the transfer of
saving and borrowing activities from life insur
ance companies to other financial institutions.
This in turn would result in less efficient alloca
tion of capital. Second, most state governments
bear part of the cost of an insurance failure by
12
providing tax credits to life insurance companies
(LICs) that pay guaranty fund assessments.
Third, losses from failures are partially borne by
insurance and pension policyholders, reducing
potential income to retirees. Finally, the experi
ences of the life insurance industry can provide
some lessons for bank regulators.
The 1980s witnessed two important changes
in the mix of LIC business: continued growth in
pension and annuity business relative to life
insurance, and a shift toward interest-rate-sensitive products. Competitive pressures led some
LICs to shift their asset portfolios from low- to
high-risk investments in order to cover the high
er rates on these new liabilities. By the end of
the decade, this strategy had begun to unravel.
The sudden but short-lived collapse of the junk
bond market and the fall in the value of commer
cial real estate reduced LIC profitability. In
reaction, LICs pulled back from the commercial
real estate market and certain segments of the
corporate bond market.
At first glance, there are many similarities
between the savings and loan and the life insur
ance industries. Both S&Ls and LICs act as
financial intermediaries and face substantial
government regulation. Life insurance policy
holders, like S&L depositors, are protected by
government-administered guaranty funds.
Elijah Brewer III is a senior economist with the
Federal Reserve Bank of Chicago. Thomas H.
Mondschean is assistant professor of economics
at DePaul University and consultant to the
Economic Research Department of the Federal
Reserve Bank of Chicago. Philip E. Strahan is an
economist with the Federal Reserve Bank of
New York.
ECONOMIC PERSPECTIVES
Because of the partial guarantee of their liabili
ties, firms in both industries have incentives to
take risk. Many have argued that regulators
exacerbated the S&L crisis by allowing thrifts to
invest heavily in high-risk loans and securities
and by not closing insolvent firms promptly,
while private creditors did not impose market
discipline on S&Ls because their deposits were
guaranteed. Yet despite the similarities between
S&Ls and LICs, the life insurance industry has
not suffered widespread failures.
In this article we explore possible explana
tions for the divergence in behavior and perfor
mance between these two classes of financial
institutions. First, we argue that in contrast to
commercial banks and LICs, S&Ls were danger
ously exposed to interest rate risk. As a result,
when nominal interest rates rose sharply in the
late 1970s, S&Ls experienced a larger decline in
the market value of their portfolios than did
LICs or banks. Then we suggest five key differ
ences that reduced the moral hazard problem for
LICs relative to S&Ls:
1) LICs possessed a larger capital cushion
than S&Ls;
2) S&L creditors had more confidence in
their government guarantees than did LIC
creditors;
3) a smaller proportion of LIC liabilities were
subject to a government guarantee;
4) LICs were subject to greater market disci
pline from uninsured creditors; and
5) LICs were subject to greater monitoring by
other LICs.
The article is organized into six sections.
First, we present financial information about the
life insurance industry both to document the
importance of LICs as financial intermediaries
and to describe the environment in which they
operate. Second, we describe the recent finan
cial problems of the industry. Third, we sketch
the regulatory framework that protects policy
holders and manages insolvencies. Fourth, we
discuss how interest rate risk differs across fi
nancial institutions. Fifth, we examine key
differences that reduced the moral hazard prob
lem for LICs compared to S&Ls. Finally, we
discuss the implications of these findings for
regulatory policy.
B a ckg ro u n d
Traditionally, life insurance companies
offer customers risk protection by agreeing to
FEDERAL RESERVE
BANK OF CHICAGO
indemnify them against losses specified in a
policy. Insurance guards against economic loss
by compensating those policyholders suffering
losses from a pool of funds paid by all policy
holders who are exposed to similar risks. At the
end of 1991, the most recent year for which data
are readily available, over 375 million policies
were in force in the United States, with coverage
totaling approximately $10 trillion. LICs’ total
1991 revenues from premium and investment
income were $411 billion.
LICs raise funds primarily from the sale of
life insurance policies, annuities, and pension
plans that have a savings feature as part of their
contract. LICs must set up reserve accounts for
the excess of the value of benefits payable in
future years over the value of the premiums to
be collected for each contract. The reserve ac
counts are divided into two types of liabilities:
(1) life insurance reserves, which cover LIC
obligations to policyholders and beneficiaries;
and (2) pension reserves, which cover expected
payments to retirees and other annuitants. These
liabilities of LICs are savings instruments by
which households can accumulate wealth for
retirement and bequests. In turn, LICs use the
premiums paid for these products to invest in
debt and equity securities. In doing so, they help
transform a large portion of the financial assets
of households into real capital investment by
businesses and governments.
Premium income from life insurance prod
ucts represented 44 percent of total gross income
of LICs in 1970 but fell to 19 percent by yearend 1991 (see table 1). Much of this decrease
occurred because traditional life insurance con
tracts with savings components offered policy
holders a substantially lower return after taxes
than did alternative investments. During the
1970s and early 1980s, rising inflation rates and
high yields on alternative investments created
greater competition for household savings. Re
turns on traditional life insurance contracts were
tied to the average rate of return on the insurer’s
portfolio. However, because LICs held a large
share of fixed-rate bonds purchased previously
at lower interest rates, the average rate of return
on their portfolio did not increase as rapidly as
market rates of interest. As a result, a large gap
emerged between prevailing interest rates and
the return on traditional LIC contracts. In addi
tion, many policyholders exercised their right to
borrow against their policies or cashed them in
for their surrender value in order to invest the
13
customers, including liberal surren
der provisions that allow withdraw
Gross income of life insurance companies
als without penalty when promised
(billions of dollars)
yields fall below benchmark rates
Source
(Cabanilla 1992). Because GICs are
1991
1980
1985
1990
of income
1970
relatively short-term liabilities, these
contracts tend to reduce the average
Life insurance
76.7
21.7
40.8
60.1
79.3
premiums
duration of insurance companies’
(44.3)a (31.2)
(25.7)
(19.1)
(19.3)
liabilities. Table 2 reports that the
3.7
22.4
53.9
129.1
123.6
Annuities 6
share of life insurance industry
(32.1)
(17.1)
(23.0)
(30.1)
(7.5)
general account assets financed by
Health insurance
GICs rose from 8.1 percent in 1986
29.4
11.4
41.8
58.2
60.9
premiums
to 10.8 percent in 1990. By year(14.8)
(23.3)
(22.5)
(17.9)
(14.5)
end 1991, however, this share had
67.9
1 1 1 .8
119.0
Investments
1 0 .1
33.9
fallen to about 8 percent, primarily
(28.9)
(2 0 .6 )
(25.9)
(29.0)
(27.8)
because some highly publicized
1 0 .2
28.2
Other
2 .1
4.3
26.3
failures caused GIC holders to shift
(4.4)
(6.5)
(6.9)
(4.3)
(3.3)
funds to alternative investments.
402.2
411.0
49.0
130.9
234.0
Total
Because the interest income
(100.0) (100.0) (100.0) (100.0)
(100.0)
credited on universal life policies
aN um bers in parentheses are the percent o f total incom e.
and other liabilities affected the
bln 1986, there w as a large increase in annuity prem ium receipts
demand for these instruments, insur
because of an N A IC -m andated change in statutory reporting.
Note: N um bers m ay not add to totals because of rounding.
ance companies have an incentive to
Source: A m erican Council of Life Insurance.
offer high rates during the early
years of these policies to attract new
customers and to forestall policy
lapses and surrenders by existing customers.
funds where they could earn higher rates. This
Wright (1991) claims that in order to maintain
created outflows of LIC funds.
the high returns being paid on GICs and other
To stem outflows and attract additional
liabilities, many insurance companies sought to
funds, LICs developed new products such as
increase interest income either by taking on
universal and variable life insurance policies.
riskier real estate loans or by reducing the quali
These differed from traditional whole life poli
ty of their corporate bond portfolios.
cies in that the size of the death benefit and/or
Historically, life insurance companies have
the annual premium could change to reflect
played an important role in the bond and mort
investment performance over the duration of the
gage markets. In 1960, they held about 50 per
policy. Such interest-rate-sensitive products
cent of all outstanding corporate bonds. While
offered new options, including the ability to
move the investment portion of the policy
among alternative assets to reflect policyholders’
TABLE 2
current preference between risk and return. As
Guaranteed investment contracts
table 1 shows, premium income from annuity
(billions of dollars)
business accounted for 30 percent of gross in
TABLE 1
come at the end of 1991, compared with only
7 percent at year-end 1970.
In addition to standard annuity products,
some life insurance companies have sold guaran
teed investment contracts (GICs). Widely used
as funding instruments for defined contribution
pension plans, GICs typically obligate an insur
ance company to repay principal and interest
accruing at a predetermined rate in a single
payment at maturity. Thus GICs have no insur
ance element. Competition for this business has
resulted in very favorable contract terms for
14
Percent
Total
o f assets
1986
67.1
8 .1
1987
74.8
8 .0
1988
105.1
1 0 .1
1989
1 2 1 .6
10.5
1990
134.6
1 0 .8
1991
130.0
8.4
Source: Am erican Council o f Life Insurance.
ECONOMIC PERSPECTIVES
this share has fallen with the growth of mutual
funds and pension plans, LICs still hold about
one-third of all corporate bonds. Within the bond
market, they are major buyers of private place
ment debt, which are securities issued in the U.S.
but not registered with the Securities and Ex
change Commission. LICs are also very active in
the commercial mortgage market, which provides
a market for loans on nonresidential properties
such as office buildings and manufacturing
plants. Together, LICs, commercial banks, and
S&Ls supply about 80 percent of the credit for all
commercial real estate loans. During the 1980s,
LICs held about 30 percent of all commercial
mortgage loans (Cabanilla 1992).
Lending in the private placement and com
mercial real estate markets requires substantial
amounts of information gathering in the form of
evaluating credit and monitoring of borrowers’
management through covenant enforcement.
Recent studies of the private placement and com
mercial real estate markets have indicated that the
loans made by LICs in these markets generally
have less uniform terms than do other invest
ments such as publicly traded corporate bonds.
As a result, private placements and mortgage
loans are less liquid. Yields are higher to reflect
information gathering costs and greater default
risk. According to data from the American
Council of Life Insurance, private placements
and mortgage loans represented about 86 percent
of new life insurance investments in 1980. At the
end of 1991, they accounted for only about 29
percent. Conversely, the share of new funds that
LICs invested in publicly traded corporate bonds
and mortgage-backed securities has been increas
ing during the 1980s and early 1990s. In 1980,
these assets accounted for about 13 percent of all
new investments of LICs. By year-end 1991, that
figure had risen to 70 percent. The shift towards
marketable and more liquid securities stemmed
from the increased securitization of debt as well
as from changes in liability structure and from
the asset quality problems of life insurers.
Life insurers' em erging
fin a n cia l p ro blem s
Table 3 examines the financial characteris
tics of LICs classified by their 1986 book value
statutory capital-asset ratios. More than threequarters of the industry’s assets were held by
LICs with capital and surplus less than 9 percent
of general account assets (low-capital LICs)3.
Low-capital LICs held greater proportions of
FEDERAL RESERVE
BANK OF CHICAGO
mortgage loans and junk bonds than did compa
nies with capital ratios above 9 percent (highcapital LICs). Guaranteed investment contracts
are a relatively more important funding source for
low-capital LICs than for high-capital companies.
Figure 1 presents the market capitalization-asset
ratios for a sample of 44 publicly traded life insur
ance companies classified as “high” junk bond
holders (9), “high” commercial mortgage loan
holders (11), and “others” (24).4 All three groups
of LICs experienced a deterioration in market
capitalization over the 1986-1990 sample period.
However, the deterioration was the greatest for
the high junk bond holders. Other things held
constant, lower market capitalization-asset ratios
at high junk bond LICs indicate a greater expo
sure to the risk of failure.
During the late 1980s and early 1990s, the
increased emphasis on nontraditional insurance
products along with shifts towards ex ante riskier
assets took its toll. Declines in the market values
of below-investment-grade bonds and commercial
real estate reduced the market value of capital of
many LICs; a few have been rendered insolvent.
Two announcements in 1990 highlighted the
industry’s emerging financial difficulties. In
January, First Executive Corporation, a large
holder of below-investment-grade bonds, an
nounced that it would take a charge of $515 mil
lion in the fourth quarter for junk bond losses.
Then in October, Travelers Corporation, one of
the largest holders of commercial real estate
loans, announced it was setting aside $650 million
in reserves for anticipated losses on its commer
cial real estate portfolio. These and similar prob
lems at other LICs led to policyholder liquidity
runs and the collapse of several large companies
such as First Executive Corporation in mid-1991.
Liquidity runs could occur because many of the
new products sold by LICs provide policyholders
with liberal withdrawal provisions in which
the holder may demand immediate payment of
principal and accrued interest. According to Fenn
and Cole (1992), holders of GICs and other inter
est-rate-sensitive products are more likely than
traditional policyholders to exercise withdrawal
options on annuity products and to borrow against
insurance products when the issuing firm appears
troubled. Surviving LICs have responded to these
financial problems by reducing their holdings of
risky assets and improving capital ratios.
The weakened condition of LICs reduced the
supply of credit in both the commercial mortgage
market and the below-investment-grade segment
15
TABLE 3
Financial characteristics of life insurance companies
(billions of dollars)
High-capital com panies3
1986
1987
1988
1989
1990
(----------------------- billions of dollars------------------------)
22.3
24.4
26.7
30.1
32.2
Junk bonds
4.7
6.7
5.6
GICs
2.3
3.4
5.3
6.8
10.2
13.8
179.7
201.2
229.7
259.0
290.5
M ortgage loans
Total general account assets
/
7.7
\
Book value o f net w o rth /
m ortgage loans
163.8
157.4
153.9
148.8
144.4
Book value o f net w o rth /
junk bonds
783.8
572.6
739.0
659.0
606.3
Book value o f net w o rth /
total assets
20.3
19.1
17.9
17.3
16.0
Low -capital com panies3
1986
1987
1988
1989
1990
(----------------------- billions of dollars----------------------- )
173.1
193.5
211.2
229.5
Junk bonds
28.9
40.3
38.9
44.7
43.3
GICs
67.6
82.4
95.7
110.0
117.7
683.6
757.1
842.1
918.2
979.1
M ortgage loans
Total general account assets
242.6
t1
/
(
Book value of net w o rth /
m ortgage loans
16.7
16.5
17.2
18.1
19.3
Book value of net w o rth /
junk bonds
100.8
79.0
93.2
93.3
108.5
Book value o f net w o rth /
total assets
4.2
4.2
4.3
4.5
4.8
aL o w -c a p ita l life in s u ra n c e c o m p a n ie s are th o s e w ith b o o k ca p ita l-a sse t ra tio s less th a n o r e q u a l to 9 p e rce n t
at th e end o f 1986. Th e re m a in in g c o m p a n ie s are c la s s ifie d as h ig h -c a p ita l.
S ource: N a tio n a l A s s o c ia tio n o f In su ra n ce C o m m is s io n e rs (N AIC ), D atabase o f A n n u a l S ta te m e n ts.
of the private placement market. Carey, et al.
(1992) show that in the below-investment-grade
segment of the private placement market, loan
volume was down and loan rates were up. The
rise in rates was not caused by a general increase
in loan risk, but rather by LICs’ flight to quality.
Corcoran (1992) also concludes that the reduced
willingness of insurance companies to make new
loans exacerbated the credit problems of the
recent recession. The deterioration of commer
cial real estate values and an increase in mort
gage delinquency rates, as illustrated in figure 2,
led LICs to reduce their exposure to both com
mercial real estate as well as the private place
ment market.
16
As a result of these problems, the industry
capital-asset ratio fell in 1990 to 8.5 percent. In
1991, the life insurance industry increased its
capital-general account asset ratio to 9.3 percent,
signalling an improved ability of firms to absorb
losses without becoming insolvent. This cush
ion should help reassure policyholders about the
solvency of LICs.
Regulation o f life in surance co m p a n ie s
Just as a capital cushion protects policy
holders and other creditors from losses at LICs,
government regulation also safeguards their
interests. Life insurance companies are regulat
ed for many of the same reasons as are other
ECONOMIC PERSPECTIVES
F IG U R E 1
Market capitalization of some LICs
p e rcent
Despite the uniform standards proposed by
the NAIC, life insurance companies are still
subject to widely varying degrees of regulatory
scrutiny. Examinations vary with the size and
sophistication of state insurance departments or
with the level of resources that states allocate to
regulation. Further, LICs vary in their ability to
lobby for less restrictive regulations or scrutiny,
and states vary in their susceptibility to such
pressures.
To protect policyholders and to manage
insolvencies, all fifty states and the District of
Columbia have established guaranty funds.
Prior to 1970, only one state had a guaranty
system to cover the obligations of life and health
insurance companies. Then in 1970, the NAIC
adopted a “model” guaranty system for subse
quent consideration by individual state legisla
tures. In addition to provisions stating what the
guaranty fund covered, the NAIC model also
allowed insurance companies to credit guaranty
fund assessment costs on their state premium
taxes. Within a year, nine states adopted legisla
tion based on or similar to the NAIC model.
Guaranty systems satisfy benefit claims of poli
cyholders and annuitants in the event that an
insolvent company lacks sufficient assets after
liquidation. Harrington (1991) claims that the
growth of these guaranty funds has contributed
to the increased number and magnitude of insol
vencies in the insurance industry in recent years.
Guaranty funds are financed by ex post
assessments on surviving insurance firms operat
ing in the particular state, with each company
financial intermediaries: first, to offset the mor
al hazard problems exacerbated by government
guarantees of LICs’ liabilities; second, to de
crease the probability that failure of one LIC
may cause policyholders at other LICs to exer
cise their surrender options after losing confi
dence in their companies’ ability to meet obliga
tions;5 and third, to protect taxpayers from
losses resulting from LIC failures.
State insurance departments are the agen
cies charged with regulating LICs. State regula
tors enforce rates, asset restrictions, and other
policies established by state legislation. If a
company wishes to write insurance in a particu
lar state, it must first receive permis
sion from the state insurance com
F IG U R E 2
missioner. Thereafter, LICs must
Delinquency rates of commercial real estate mortgages
provide regulators with income
statement and balance sheet infor
p ercent
mation annually. In addition, state
insurance departments usually audit
companies operating within their
borders once every three years.
Most states levy a tax on insurance
premiums to finance part of the cost
of regulation. The National Associ
ation of Insurance Commissioners
(NAIC) also monitors LICs by per
forming annual computerized audits.
Companies failing four or more of
eleven NAIC audit ratio tests face
increased monitoring from state
regulators (see Cummins 1988 for
more details).
FEDERAL RESERVE
BANK OF CHICAGO
17
paying an assessment based on its share of total
premium income. As of December 31,1992, in
39 states, LICs may offset assessments against
their state taxes, thereby shifting the cost of
failure directly onto state taxpayers. In the re
maining states, LICs may impose a premium
surcharge to cover the cost of the assessment.
In most states, coverage under guaranty
funds is $300,000 in death benefits, $100,000 in
cash or withdrawal value for life insurance,
$100,000 in present value of annuity benefits,
and $100,000 in health benefits. Some states
cover all insurance policies written by an insol
vent firm located in the state; others cover the
policies of residents only. In the case of unallo
cated annuities such as GICs purchased by com
panies to fund pension plans, some states cover
up to a certain amount, usually $5 million. Oth
er states, such as California, Massachusetts, and
Missouri, do not cover GICs.
Because of variations in state guaranty
funds and in the way insolvencies are handled,
the parties bearing the costs of an insurance
failure differ across states. Surviving insurance
companies initially pay their assessments and
claim them as an expense on their federal corpo
rate income tax return, reducing their federal
income taxes. As companies receive tax credits
in subsequent years, these credits become tax
able income. As a result, the federal government
bears part of the cost of an insolvency since it
does not fully recover the present value of the
tax decrease granted in the assessment year. In
states with premium tax offsets, however, the
majority of the cost is paid by state taxpayers.
A study of 1990 life/health guaranty fund assess
ments found that 73.6 percent was paid by state
taxpayers, 8.9 percent by federal taxpayers, and
17.5 percent by the equity holders of the surviv
ing firms.6
The way in which state guaranty systems
manage insolvencies raises several policy con
cerns. First, LICs pay nothing ex ante to receive
the guarantees. Assessments are based on the ex
post cost of a given failure and bear no relation
ship to current or future LIC risk exposure. Sec
ond, companies in states with premium tax off
sets have little incentive to monitor each other,
since over 80 percent of the assessment will be
recouped through lower taxes. Third, insurance
guaranty funds reduce the incentive for policy
holders to exercise market discipline. In the
absence of guaranty funds, policyholders would
have more incentive to buy from safe LICs or to
18
demand lower premiums from high-risk firms.
As the S&L crisis demonstrated, government
guarantees of firm liabilities could create a mor
al hazard problem. If these guarantees are mis
priced, institutions with low net worth may have
strong incentives to gamble for resurrection by
investing in riskier assets.7
Interest rate risk at
fin a n cia l in stitu tio n s
The value of LIC portfolios has traditionally
been relatively insensitive to changes in interest
rates.8 A large proportion of LICs’ liabilities
consists of life insurance reserves, and most of
the payments for these products occur in the
distant future. Most LIC assets consist of long
term corporate debt, mortgages, and long-term
government securities. In the absence of credit
risk, both the nominal death benefits and the
payoff of these long-term assets are determined
at the outset. As a result, the firm is less ex
posed to unanticipated changes in interest rates.
If the firm decides to hold short-term assets such
as Treasury bills or commercial paper against
life insurance policies, it would have no guaran
tee that its portfolio could support future claims.
Declines in interest rates would reduce the
firm’s earnings and its ability to meet future
obligations.
Regulation of savings institutions, on the
other hand, has encouraged these firms to hold
long-term, fixed-rate mortgage loans financed
with short-term deposits. This strategy worked
well during the period of stable interest rates
from the end of World War II to the 1960s. But
S&Ls remained vulnerable to changes in the
level of interest rates. Because of Regulation Q
interest rate ceilings, S&Ls were prevented from
offering depositors competitive rates when mar
ket interest rates rose above the ceiling rate.
When this occurred, many depositors withdrew
their funds in order to invest them in higheryielding money market instruments, which
caused outflows of S&L deposits. To stem the
outflow, S&Ls were allowed to offer several
deposit products not subject to Regulation Q
ceilings. However, because over 80 percent of
S&L assets were invested in long-term, fixedrate mortgage loans made previously at lower
rates, their interest income did not increase as
rapidly as their cost of funds. As a result, S&Ls
suffered negative interest rate margins. This
predicament—interest rate risk— is particularly
characteristic of the S&L industry. Figure 3
ECONOMIC PERSPECTIVES
compares the capital-asset ratios for the S&L
and life insurance industries. Between 1978 and
1982, the S&L capital ratio fell from 5.6 to 0.6
percent but the LIC capital ratio actually rose
from 8.3 to 9.1. Since there is a better corre
spondence between the durations of assets and
liabilities of LICs, these institutions were less
exposed to interest rate risk; hence, they did not
experience the large losses and subsequent de
clines in capital as a result of high nominal inter
est rates from 1978 to 1982.
To judge a firm’s exposure to interest rate
risk, we use stock market data. The stock re
turns of financial institutions depend on many
economic variables besides interest rates, such as
expectations of future economic conditions,
future investment opportunities, productivity,
and tax policies. Using a two-factor market
model from the finance literature, we relate the
return on a portfolio of each type of institution to
the return on an index of the overall stock mar
ket and the return on a portfolio of long-term
government securities. The following equation
allows us to compare the relative exposure of the
three types of financial institutions to interest
rate risk:
(')
h ,
- aj +
+ E
j,t
where
Rj t = return on financial institution j at t,
R ,., = return on stock market,
Rj t = return on portfolio of long-term
government bonds.
The variable R .., controls for all economic
variables that would affect profits for all corpo
rations. The value of the second variable, Rf
depends solely on interest rates, so its coefficient
provides an estimate of the interest rate sensitivi
ty of each type of financial institution.
We estimated equation 1 using monthly
returns for two sample periods, 1972-1982 and
1983-1991. We split the sample at the end of
1982 for several reasons. During the first
period, S&Ls and banks faced governmentmandated interest rate ceilings. After the pas
sage of the Depository Institutions Deregulation
and Monetary Control Act of 1980, these regula
tions began to be phased out. Moreover, the
Gam-St Germain Depository Institutions Act of
1982 substantially liberalized S&L asset-holding
FEDERAL RESERVE
BANK OF CHICAGO
FIGURE 3
Capital-asset ratios
p e rcent
Note: The m easures of capital used are statutory
capital for LICs and tangible capital for S&Ls.
Sources: Am erican Council of Life Insurance and
O ffice of Thrift Supervision.
powers. Both of these laws allowed S&Ls to
reduce interest rate risk. Also, the market value
of S&L capital dropped sharply during the 19811982 period. Brickley and James (1986) show
that stock returns for poorly capitalized firms
may respond less to economic variables since
the deposit insurer bears the brunt of all losses.
The results of estimating equation 1 appear
in table 4. They show that S&Ls were much
more exposed to interest rate fluctuations than
either banks or LICs. In the first sample period,
for instance, interest rate changes did not signifi
cantly influence the stock returns of LICs. By
contrast, S&L stock returns were highly sensi
tive to those changes. For example, the estimat
ed coefficient shows that S&L stock returns
exhibited 90 percent as much sensitivity to inter
est rate changes as did a portfolio of twenty-year
government bonds. In fact, one cannot reject the
null hypothesis that during the 1972-1982 peri
od, S&L stock prices were as sensitive to interest
rates as were long-term government bond prices.
Flannery and James (1984) show that the
degree of sensitivity of bank stock returns to
interest rates depends directly on the duration
mismatch between its assets and liabilities.
Since life insurance companies actively try to
match the maturity of both sides of their balance
sheet, it is not surprising that LIC stock returns
exhibit little interest rate sensitivity.
In the second sample period, the interest
rate sensitivity of S&L stocks decreased from
19
TABLE 4
Estimates of interest rate sensitivity for portfolios of commercial bank,
savings and loan, and life insurance stocks3
Industry
Intercept
Return on
market
portfolio
Return on
government
bond portfolio
R2
Durbin-Watson
statistic
1972-1982
Savings and loans
-0.003
(0.004)b
1.030*
(0.066)
0.904*
(0.128)
75.4%
2.185
Commercial banks
0.001
(0.002)
0.510*
(0.029)
0.150*
(0.056)
75.4%
1.866
Life insurance
0.001
(0.002)
0.707*
(0.030)
0.074
(0.057)
84.0%
1.819
Savings and loans
-0.010
(0.004)
0.996*
(0.077)
0.484*
(0.125)
65.6%
1.622
Commercial banks
0.003
(0.003)
0.662*
(0.046)
0.154
(0.075)
67.8%
1.378
Life insurance
0.002
(0.002)
0.722*
(0.038)
0.164*
(0.062)
79.1%
1.618
1983-1991
aThe m o n th ly p o rtfo lio o f returns fo r each indu stry includes all pu blicly traded stocks on the New York and
Am erican Stock Exchanges and the NASDAQ. The data are fro m the Center fo r Research in Securities Prices
(CRSP). The market index is the m o n th ly return on an equally w eighted p o rtfo lio o f all stocks on the three
exchanges, inclusive o f dividends. The interest rate index is the m o nthly return on a p o rtfo lio o f long-term
go vernm ent bonds w ith m a tu rity o f ap proxim ately 20 years. These tw o indices are also fro m CRSP.
bStandard errors appear in parentheses.
•s ig n ific a n t at the .01 level.
0.90 to 0.48, while neither the bank nor the LIC
interest rate sensitivity changed significantly
from the first sample period. Evidently, the
deregulation the S&L industry may have had the
intended effect of reducing but not eliminating
interest rate risk. However, with S&L industry
capital at historic lows during this period, the
lack of responsiveness of stock returns to interest
rate volatility may reflect the put protection
afforded by deposit insurance. As a firm’s capi
tal approaches zero, further declines will be
reflected in increased deposit insurer liability
rather than in stock returns. Since the capital of
LICs and banks did not fall to the same degree in
the 1980s, those institutions apparently did not
experience a similar decline in interest rate sen
sitivity. In fact, for LICs the point estimate
actually increases from 0.07 to 0.16, although
this difference is not statistically significant.
These results indicate that S&Ls were
uniquely vulnerable to interest rate movements
in the 1970s. We attribute the weakness of this
industry to regulations that encouraged savings
institutions to hold an unbalanced book. In
20
contrast, both LICs and commercial banks have
been permitted to hold a sufficiently broad array
of assets to facilitate better diversification.
M oral hazard at fin a n cia l in stitu tio n s
Insurers have long dealt with moral hazard.
By its very nature, insurance reduces the costs
associated with a particular bad outcome and thus
weakens the purchaser’s incentive to take costly
self protective actions. For instance, holders of
fire insurance have less incentive to buy fire
extinguishers to protect their property than do
uninsured individuals. In private markets, one
way in which insurers mitigate this problem is by
adding deductibles and copayments to policies.
In the case of financial institutions, government
liability guarantees weaken the incentive for
creditors to discipline the propensity of firms to
bear additional risk; fully insured depositors with
confidence in the Federal Deposit Insurance
Corporation (FDIC) will not waste time monitor
ing their banks’ investment decisions. Effective
monitoring by regulators and/or other firms can
mitigate this moral hazard problem.
ECONOMIC PERSPECTIVES
Many analysts have argued that the S&L
crisis occurred because government regulators
did not control the moral hazard inherent in
fixed-premium deposit insurance.9 Regulatory
oversight declined during the 1980s. Insolvent
S&Ls that were permitted to remain in operation
were not monitored very closely. In addition,
S&Ls were given new rights to invest in high-risk
assets such as junk bonds and acquisition and
development loans. In pursuit of high profits,
many S&Ls responded by collecting federally
insured deposits and investing them in high-risk,
high-expected-retum assets. This action deep
ened the insolvency problems. As a result, be
tween 1987 and 1992 over 800 S&Ls were re
solved by the Federal Savings and Loan Insur
ance Corporation (FSLIC) and later the Resolu
tion Trust Corporation.
Brewer and Mondschean (1993b) show
empirically that life insurance companies face
similar moral hazard problems. They found that
over the 1986-90 period, low-capital LICs experi
enced one-time increases in market value capital
following a shift from low-risk assets to high-risk
assets such as real estate direct investment and
equity issues. As expected, increases in risky
assets did not have a statistically significant effect
on the market value of high-capital LICs.
Brewer and Mondschean (1993c) also show
that the largest LICs that failed in 1991 had siz
able exposures to junk bonds. In fact, their expo
sure was so large that a decline of 12 to 14 per
cent in the value of their junk bond portfolio was
sufficient to wipe out their book capital complete
ly. These findings are consistent with a moral
hazard problem associated with government
liability insurance.
In response to declining asset values, both
LICs and S&Ls were forced to set aside funds to
reserve against losses on securities and loans.
However, regulators anticipate spending over
$200 billion of taxpayers’ money to resolve the
S&L debacle, while the cost of managing insol
vent LICs should be much less. We suggest that
five key differences between the environment in
which LICs operated relative to S&Ls reduced
the moral hazard problem sufficiently to prevent
a crisis in the life insurance industry.
Vulnerability to capital shocks
S&Ls faced a massive capital shock when
interest rates skyrocketed in the early 1980s.
In addition, regulators lowered the minimum
capital requirements all S&Ls had to meet.
FEDERAL RESERVE
BANK OF CHICAGO
Neither banks nor LICs faced a comparable
decline in net worth.
As capital declines or capital forbearance
grows, a firm has an increasing incentive to
pursue an aggressive strategy. This is because
the firm’s capital acts as a deductible payment in
a traditional insurance arrangement. In this
context, the chance of losing the value of the
owners’ stake in the firm reduces the incentive
to hold risky assets.10 A firm with little or no
capital, however, has little or nothing to lose by
pursuing a gambling strategy. This explains
why many insolvent S&Ls invested heavily in
junk bonds during the 1980s. If the investments
paid off, the institution’s owners reaped the
rewards; if the returns were low, the losses were
passed on to the deposit insurer.
Figure 3 compares S&L and LIC book
value capital ratios from 1975 to 1991. LIC
capital ratios fluctuated between 8.0 and 9.3
percent over the period but exhibited little trend.
By contrast, S&L capital ratios, computed using
tangible accounting principles, fell sharply after
the 1979-1982 recession. Since S&Ls are more
exposed to interest rate changes than banks or
LICs, they suffered massive losses when interest
rates rose in the late 1970s and early 1980s.
This capital shock exacerbated the moral hazard
problem.
Federal versus state guarantees
S&Ls’ guarantees are administered by the
federal government and carry the implicit back
ing of the U.S. Treasury. This fact is widely
known and inspires near-universal confidence.
By contrast, LICs’ guarantees are administered
by their respective states and carry no compara
ble backing. These guarantees are not as well
publicized as federal deposit insurance and seem
to inspire less confidence in policyholders. As a
result, insurance companies are more sensitive to
the impact of poor financial health and asset risk
on their ability to raise funds.
Three cases from the life insurance industry
support this interpretation. Mutual Benefit of
New Jersey, like other LICs in that state, had no
government guarantee on its liabilties. In early
1991, the company’s asset quality problems led
its GIC holders to surrender their contracts. The
asset writedowns at First Executive Corporation
in early 1990 were followed by policyholder
liquidity runs at its life insurance subsidiaries in
New York and California. Apparently lacking
faith in the guaranty fund system, policyholders
21
increased their surrender requests from the New
York subsidiary after the regulatory seizure of
First Executive Corporation’s California unit in
April 1991. Another New York example is the
case of Mutual Life Insurance Company of New
York (MONY). Despite the existence of a guar
anty fund, policy and contract holders withdrew
more than $900 million during the third quarter
of 1990, reflecting concern about MONY’s large
real estate exposure. Similar liquidity runs oc
curred at S&Ls in Ohio and Maryland that were
covered by state deposit insurance funds.
No such panic has occurred in federally
insured S&Ls. Depositor confidence in the
FSLIC, or at least in the implicit backing of the
U.S. Treasury, has remained sufficiently high to
prevent runs.1
1
Breadth o f coverage
Because of the breadth of de facto coverage,
S&Ls are able to use fully insured deposits as
their primary source of funds. Congress in
creased deposit insurance coverage in 1981 to
$ 100,000 per depositor per institution. More
over, all uninsured depositors have received full
reimbursement in resolutions not culminating in
liquidation. Some of the asset growth by S&Ls
in the 1980s was financed by brokered deposits.
These funds allowed S&Ls to draw deposits from
the national market without giving up the benefit
of federal deposit insurance coverage.
By contrast, while some LICs used GICs and
single premium deferred annuities (SPDAs)
during the 1980s to facilitate growth, these instru
ments have not received the same level of gov
ernment backing as did brokered S&L deposits.1
2
In several cases, failure resolutions have imposed
losses on LIC creditors in the form of delays in
repayment and loss of interest. Unlike traditional
life insurance products, GICs and SPDAs could
be put back to the company at face value. This
fact helps explain why the run on Mutual Benefit
of New Jersey was started by GIC holders.
Monitoring
Financial institutions may face losses as a
result of the failure of a competing institution. In
the deposit insurance system, all banks and S&Ls
pay upfront for deposit insurance. LIC state
guaranty funds make these losses explicit in that
surviving LICs pay the costs of a resolution.
LICs can reduce these costs by pressuring regula
tors to tighten enforcement of safety and sound
ness regulations. In some states, LICs can also
pass resolution costs on to taxpayers through
22
premium tax credits. Brewer, Mondschean, and
Strahan (1992) found that in states where premi
um tax credits do not exist, LICs hold safer port
folios. This is strong evidence that when guaran
ty systems provide incentives for self-monitoring,
they reduce risk-taking and increase industry
stability. Calomiris (1989) reached a similar
conclusion in his study of antebellum deposit
insurance systems. He found that self-regulating
mutual liability systems achieved stability and
survived financial panics.
Free rider problems
The size of a government insurance fund
may also influence the behavior of its members.
Larger systems will face greater free rider prob
lems, which lead to less monitoring and weaker
enforcement of regulations. As noted earlier, in
state guaranty systems, surviving firms pay the
costs in the event of failure. In the federal deposit
insurance system, taxpayers provide financial
backing, yet member institutions also bear some
of the costs associated with widespread failures.
In fact, the FDIC tripled its fees in the aftermath
of the FSLIC’s bankruptcy and the deterioration
of the reserves in the Bank Insurance Fund. Thus
in both systems, firms have an incentive to reduce
the costs associated with these government guar
antees. But individual firms have more at stake
in smaller, state-administered life insurance guar
anty funds. As a result, LICs have a greater in
centive to pressure regulators to enforce con
straints on high-risk behavior.1
3
C o n c lu sio n s and p o licy p re scrip tio n s
The recent failures of several large insurance
companies have raised concerns about the sound
ness of the life insurance industry. The industry’s
overall portfolio risk appears to have increased
during the 1980s. Moreover, LICs with lower
capital ratios have higher concentrations of junk
bonds and commercial real estate than do wellcapitalized LICs. In response to the liquidity
runs in the early 1990s, the life insurance industry
has restored profitability and raised new capital.
The experiences of the life insurance industry
stand in stark contrast to the disastrous problems
that S&Ls experienced and suggest some conclu
sions about how to contain risk-taking of deposi
tory institutions.
Like S&Ls and banks, life insurance compa
nies may succumb to moral hazard because gov
ernment guarantees weaken the incentive for
creditors to constrain firm risk-taking. Our re
search indicates that the use of premium tax
ECONOMIC PERSPECTIVES
offsets for guaranty fund assessments encourages
LICs to increase portfolio risk. In addition, con
cerns about liquidity runs have caused LICs to
reduce their holdings of risky assets and improve
capital ratios. These findings suggest a number
of policy prescriptions that could help improve
the safety and soundness of the life insurance
industry. First, since government backing makes
life insurance policies more attractive, LICs
should pay for access to the guarantees. Premium
tax offsets for the costs of resolving failures tend
to lead to less industry monitoring because surviv
ing LICs can pass a larger portion of the costs of
resolving failures onto taxpayers. These offsets
should be eliminated. Finally, regulators could
increase market discipline by encouraging LICs
to finance a portion of their assets with puttable,
uninsured liabilities such as guaranteed invest
ment contracts.
Despite these weaknesses in the regulatory
structure of LICs, it also contains strengths that
should be extended where possible to depository
institutions. For instance, risk-taking may be
contained by encouraging financial institutions to
monitor each other and thus reduce the need for
costly regulation. What is crucial is aligning the
incentives of taxpayers and financial institutions
to reduce the cost of government guarantees.
We believe that state guaranty funds create fewer
incentive problems than does deposit insurance
because they encourage self-monitoring to mini
mize the potential costs of LIC failures. The
behavior of financial institutions also may be
more effectively controlled by complementing
regulatory oversight with market discipline.
Discipline could be imposed by a specific class
of creditors which is willing to monitor financial
institution risk and bear the risk of loss.
The FDIC Improvement Act of 1991
(FDICIA) extends some of the features that exist
in the LIC industry to depository institutions.
The act improves monitoring with the require
ment that all depository institutions, regardless
of size, that are determined to have insufficient
capital must be closed, recapitalized, or other
wise restructured. These provisions for prompt
corrective action allow bank regulatory agencies
to intervene early and thus reduce the exposure
of the deposit insurance fund to losses. Other
provisions of the act authorize the FDIC to im
plement a system of risk-based deposit insurance
with premiums related, in part, to the cost of
future bank failures. Thus banks have greater
incentives to monitor each other to keep deposit
insurance assessments down. As the experience
of the life insurance industry has indicated,
private monitoring can reduce the cost of gov
ernment guarantees.
FOOTNOTES
'See Resolution Trust Corporation (1993).
2The term life insurance company refers throughout this
article to firms classified as life and/or life-health insurance
companies.
3General account assets equals total assets minus separate
account assets. Separate accounts are defined as groups of
assets designed as backing for specific obligations in which
the investment risk is borne by the policyholder, and the
insurer’s guarantee is limited to mortality and expense
charges (see Saunders 1986).
4To be considered a “high” junk bondholder, an LIC in our
sample must have a junk bond-asset ratio o f 6.6 percent, the
industry average at year-end 1990. The remaining LICs
were classified as “high” commercial mortgage loan hold
ers if their commercial loan-asset ratio was greater than or
equal to 21.6 percent, the industry-wide average at the end
o f 1990. The rest were classified as “others.”
5Fenn and Cole (1992) analyze the impact o f policyholder
behavior on the market value o f insurance companies in the
event o f an insolvency.
6See Barrese and Nelson (1992).
7Harrington (1991) makes this point for property-casualty
companies, which also benefit from state guaranty funds.
FEDERAL RESERVE BANK
OF CHICAGO
8LICs were not immune to the effects o f high interest
rates. Because insurance policyholders had incentives
to take out policy loans at below-market interest rates,
LICs suffered from disintermediation. (Curry and
Warshawsky 1986).
9See Kane (1989) for a discussion of the theory o f moral
hazard as applied to S&Ls. For empirical evidence on the
subject, see Brewer and Mondschean (1993a) and Barth,
Bartholomew, and Labich (1989).
l0See Furlong and Keeley (1989) for an analytical deriva
tion of this result.
"There is some evidence o f a loss of confidence in FSLIC
insurance. Both Brewer and Mondschean (1992) and
Strahan (1993) show that weak S&Ls paid higher rates for
both wholesale and retail deposits than did well-capitalized
institutions. Moreover, Strahan shows that weak S&Ls that
did not raise their rates faced deposit outflows.
12Todd and Wallace (1992) detail the growth of GICs and
SPDAs during the 1980s.
l3These free rider problems may be contained by organiza
tions such as the Community and Savings Banks o f Ameri
ca and the American Bankers Association.
23
REFERENCES
Barrese, James, and Jack M. Nelson, “Distributing
Corcoran, Patrick J., “The credit slowdown of
the cost of protecting life-health insurance consum
ers,” The College of Insurance, unpublished paper,
April 1992.
c e e d in g s o f a C o n f e r e n c e o n B a n k S tr u c tu r e a n d
Barth, James, Philip J. Bartholomew, and Carol
Labich, “Moral hazard and the thrift crisis: an analy
sis of the 1988 resolutions,”
P r o c e e d in g s o f a C o n
f e r e n c e o n B a n k S tr u c tu r e a n d C o m p e titio n , Federal
1989-1991: the role of supply and demand,”
P ro
Federal Reserve Bank of Chicago,
1992, pp. 445-462.
C o m p e titio n ,
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24
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