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NOVEMBER/DECEMBER 1 9 8 9

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l l

ECONOMIC PERSPEC1 r m i S
A review from the
Federal Reserve Bank
of Chicago

. V, ■

F u ll-b lo w n crisis,
h a lf-m e a s u re cu re
In d ex fo r 1 9 8 9

C all fo r papers

In v e s tm e n t c y c lic a lity in
m a n u fa c tu rin g in d u s trie s

FEDERAL RESERVE BAN K
OF
 CHICAGO


Conference on
Bank Structure
& Competition

1990

Contents
F u ll-b lo w n crisis,
h a lf-m e a s u re c u r e ............................................................................................ 2
Elijah B rew er III

FIRREA’S fifty billion dollars is serious money,
but not serious enough to clean up fully and finally
all the factors in the S&L mess—the financial
services industry needs some restructuring

In d ex fo r 1 9 8 9

17

C all fo r c o n fe re n c e papers

18

In v e s tm e n t c y c lic a lity in
m a n u fa c tu rin g in d u s tr ie s ........................................................................... 19
Bruce C. Petersen and W illia m A . Strauss

In looking at industrial investment and GNP,
it may be more important to see
the individual trees than the whole forest

ECONOMIC PERSPEC TIV ES

NOVEMBER/DECEMBER 1989 Volum e XIII, Issue 6

Karl A. Scheld, Senior Vice President and
Director of Research

ECONOM IC PERSPECTIVES is published by
the Research Department o f the Federal Reserve
Bank o f Chicago. The views expressed are the
authors' and do not necessarily reflect the views
o f the management of the Federal Reserve Bank.
Single-copy subscriptions are available free
of charge. Please send requests for single- and
multiple-copy subscriptions, back issues, and
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Chicago, Illinois 60690-0834, or telephone (312)
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Articles may be reprinted provided source is
credited and The Public Information Center is
provided with a copy of the published material.

Editorial direction
Edward G. Nash, editor, David R. Allardice, regional
studies, Herbert Baer, financial structure and regulation,
Steven Strongin, monetary policy,
Anne Weaver, administration
Production
Nancy Ahlstrom, typesetting coordinator,
Rita Molloy, Yvonne Peeples, typesetters,
Kathleen Solotroff, graphics coordinator
Roger Thryselius, Thomas O ’Connell,
Lynn Busby, graphics
Chris Cacci, design consultant,
Kathryn Moran, assistant editor




ISSN 0164-0682

F u ll-b lo w n c ris is ,
h a lf-m e a su re c u re

The new rescue bill provides some relief
for S&Ls. Still needed to cure the ailing
industry: Market-value accounting,
risk-based deposit insurance, and
market discipline on S&L management

Elijah B rew er III

The shortfall in the savings
and loan (S&L) deposit insur­
ance fund has been estimated
to be in the $100-120 billion
range, and possibly more.1
Regulators are concerned about the adequacy
of the $50 billion provided in the S&L rescue
bill to resolve current insolvencies over the
next three years.
The rapid deterioration in the financial
condition of the S&L industry over the last
decade has raised concern about the causes of
the problems and the appropriate policy re­
sponses to those problems. Unfavorable eco­
nomic conditions in certain sectors of the
country can partially explain the weakened
health of the S&L industry, but many analysts
argue that other factors are also responsible.
Interest-rate risk and deregulation; the broad­
ened investment powers granted S&Ls in 1982
by the passage of the Gam-St Germain Act;
inadequate supervision; mispriced deposit
insurance; and the government’s failure to deal
with the undercapitalization in the industry
have all been cited as contributing to the in­
dustry’s dismal performance during the 1980s.
There is a growing concern that the S&L res­
cue package offers little promise of providing
a permanent solution to the problem.
This article discusses the S&L crisis,
reviews some past research, and presents new
evidence on the causes of the problems. The
findings should aid legislators and regulators
in further restructuring the S&L industry. The
first section discusses the nature and magni­

2



tude of the S&L crisis. The second section
discusses the consequences for the S&L indus­
try of holding specialized portfolios that are
exposed to interest-rate risk. The third section
examines the effect of deregulation on the cost
of deposits. The fourth section analyzes for­
bearance as a public policy response toward
failing institutions. The fifth section examines
the risk implications of nonmortgage invest­
ments. New evidence, as well as previous
research, regarding the riskiness of mortgage
and nonmortgage activities are presented in
this section. A discussion of the reform legis­
lation is contained in the final section.
The S & L crisis

Savings and loan associations have his­
torically specialized in home mortgages, and
their initial problems arose from this tradition.
Until 1978 the S&L industry was (generally)
profitable. Except for relatively short periods
of tight money around 1966, 1969, and 1974,
the average rate paid by S&Ls on short-term
deposits was significantly below the average
yield on their longer-term assets. Those were
prosperous years for S&Ls, and their share of
deposits rose steadily between 1946 and 1978.
The period after 1978 marked the begin­
ning of an era of higher interest rates that
greatly increased the cost of funds without
increasing revenues from mortgage loans commensurately. The result was a period of proElijah Brewer III is an econom ist at the Federal
Reserve Bank of Chicago.

ECONOMIC PERSPECTIVES

tracted losses for large numbers of S&Ls dur­
ing the early 1980s.
The extent of these losses was demon­
strated by the events of 1982. Using regula­
tory accounting principles (RAP), recorded
after-tax industry losses were about $4 billion
in that year. This was the first time the S&L
industry suffered two consecutive years of
annual accounting losses since the Federal
Savings and Loan Insurance Corporation
(FSLIC) was established in the early 1930s.
Book net worth, as calculated by RAP, fell by
over 8 percent. However, this fall in book net
worth understates the true decline in S&L
capital.
Book net worth can be misleading when
current market values of assets and liabilities
differ from their historical values. Such differ­
ences can result from, for example, changes in
interest rates.2 Figure 1 depicts estimates of
three book-value measures and one marketvalue measure of capital. The book-value
measures are RAP, generally accepted ac­
counting principles (GAAP), and tangible
accounting principles (TAP), and the marketvalue measure is labeled MVA.
The measured decline in net worth is the
least when capital is measured according to
RAP. Regulatory accounting principles allow
S&Ls to count as part of capital net worth
certificates (paper issued by the Federal Home
Loan Bank Board to increase recorded, though
not economic, net worth), appraised equity
capital, and qualifying subordinated deben­
tures, and to defer losses on the sale of assets
that bear below-market interest rates. At yearend 1982, regulatory net worth of the industry
was $25.3 billion compared with $27.8 billion
at the end of 1981. Net worth computed ac­
cording to generally accepted accounting prin­
ciples, however, declined from $27.1 billion in
December 1981 to $20.2 billion in December
1982. When net worth is calculated by TAP
standards, goodwill and other intangible assets
are excluded to arrive at the tangible net
worth.3 By this capital measure, net worth
declined from $25.5 billion in December 1981
to $3.7 billion at the end of 1982. Further, net
worth measured in MVA terms and adjusted
for goodwill shows that the industry was insol­
vent throughout the 1980s, reaching a deficit
of $101 billion at the end of 1982 (see Box on
calculation).4

FEDERAL RESERVE



BANK OF CHICAGO

FIGURE 1

During the early 1980s, Congress and
regulators responded to these problems by
deregulating and allowing insolvent S&Ls to
remain open—a practice known as forbear­
ance. Congress phased out the deposit-rate
ceilings for S&Ls and other depository institu­
tions, and allowed S&Ls to expand their fi-

3

Market-value calculation
Market value of net worth is calculated using
the concept reported by Kopcke (1981). On the
asset side, only fixed-rate mortgages were
marked to market. Adjustable-rate mortgages
were valued at book. Securities, the next largest
category of assets, were not revalued because a
large portion of S&L investments were eligible to
satisfy liquidity requirements, suggesting that
they have maturities of one year or less. The
“other asset” category was valued at book. For
fixed-rate mortgage loans, the average portfolio
yield is used to calculated an annual payment for
the fixed-rate portion of the mortgage loan portfo­
lio (C) using a 30-year amortization formula.
Then the following formula is used to mark these
loans to market:
..

.i—
i

CVA = ^
/= i

.f

./ —
I

+ x(1~x)
(1 + R M )'

(1 + R M ) ‘

P
'

where CVA denotes current value, x the rate
of prepayment of loans (5, 10, or 15 percent), RM
is the current mortgage rate, and P is the out­
standing principal i years hence according to the
amortization formula’s schedule. The current

nance activities beyond home mortgages. The
intent was to assure adequate deposits and
allow S&Ls to diversify so they could protect
themselves against losses caused by volatile
interest rates and housing market downturns.
Beginning in 1982, congressionally mandated
capital forbearance programs allowed weak
(high-risk) S&Ls to continue to operate uncon­
strained by capital requirements applied to
healthy S&Ls. This policy was initiated in the
hope that these S&Ls, given time, would initi­
ate strategies that would return them to capital
adequacy. With little capital at risk, however,
such S&Ls had strong incentives to engage in
riskier activities funded by their insured depos­
its, especially with a flat-rate insurance pre­
mium and a relatively risk-insensitive capital
requirement.
Since December 1982, adjusted MVA net
worth has significantly improved due to lower
interest rates, but still remained negative at the
end of 1988. By December 1988, regulatory
net worth rose to $64.5 billion, GAAP net

4



value of the loan portfolio is the discounted value
of interest payments, scheduled principal pay­
ments, and prepayments of principal.
Liabilities were not revalued because most
were either subject to immediate withdrawal, e.g.,
savings deposits, or paid interest rates close to
market rates. Although mortgage loans com­
monly are written for 15 to 30 years, many loans
are paid much sooner when borrowers sell their
houses, refinance their loans, or prepay the loan
principal. During the 1970s, many assumed that
the effective maturity of an average mortgage
loan ranged from 7 to 12 years. The 15 percent
turnover ratio refers to a mortgage portfolio that
has a 4 1/2-year half-life. The 10 percent turn­
over refers to a 6 1/2-year half-life and 5 percent
represents a 13-year half-life. For mortgage
loans, we used a 10 percent turnover ratio for
each year. See Richard W. Kopcke, “The Condi­
tion of Massachusetts Savings Banks and Califor­
nia Savings and Loan Associations,” in The
Future of The Thrift Industry, Federal Reserve
Bank of Boston Conference Series No. 24,
October 1981.

worth rose to $53.6 billion, and TAP net
worth, though showing a similar improvement,
had not yet reached its 1980 level. However,
capital forbearance policies were not an essen­
tial element in this improvement in capital
levels. The decline in interest rates since the
end of 1982 has, at least temporarily, lessened
the interest rate exposure.
The deterioration in MVA net worth since
the end of 1986 has come over a period of
substantially greater exposure to credit risk.
Unlike the larger aggregate deficit and greater
number of economic S&L insolvencies of the
early 1980s, the deficit and insolvencies of the
late 1980s are almost entirely a reflection of
poor credit quality and are unlikely, under
almost any reasonable scenario, to be reversed
in the near future.
The book-value measures of net worth
have masked the current magnitude of the
problem in the S&L industry. Market-value
net worth provides a better picture of the fi­
nancial difficulties and risk exposure of the de­
posit insurance fund.

ECONOMIC PERSPECTIVES

Legislation signed by the President in
August 1989 is designed to deal with these
financial difficulties (see Box on the law).
The Financial Institutions Reform, Recovery
and Enforcement Act of 1989 (FIRREA) will
substantially overhaul the regulatory mecha­
nism to enable regulators to more effectively
limit risk-taking by authorizing the Federal
Deposit Insurance Corporation (FDIC) to be­
come the administrative agency for two sepa­
rate deposit insurance funds; dismantling the
Federal Home Loan Bank Board (FHLBB);
transferring all S&L regulatory functions to a
new Treasury Department agency; separating
the deposit insurer from the chartering agency;
and creating a new federal government agency
to oversee the Federal Home Loan Bank
(FHLB) system. The act requires S&Ls to
increase their emphasis on residential mort­
gage lending and imposes restrictions on the
assets that are eligible to be purchased by
S&Ls. In addition, the act greatly strengthens
the civil and criminal enforcement powers of
regulators. FIRREA deals with the lack of
tangible capital in the industry by requiring all
S&Ls to satisfy a tougher capital standard by
the end of 1994. The failure in the past to
close decapitalized S&Ls contributed to the
magnitude of the current problems.
The rest of this article will take a look at
FIRREA in light of what actually went wrong.
The first step is to discuss interest-rate risk and
the progress that S&Ls have made in reducing
this risk exposure. Balance sheet and income/
expense data will be examined for S&Ls na­
tionwide and in six states (California, Florida,
Illinois, Louisiana, Oklahoma, and Texas) that
have accounted for the largest share of the
total cost of all resolutions from 1980 through
1988.5 It will be seen that portfolio specializa­
tion and high and volatile interest rates were
the causes of the S&L crisis in the early 1980s.
Next, by discussing implicit deposit interest
rates, it will be seen that the impact of interestrate deregulation has been overstated. S&Ls
could have paid substantially higher explicit
rates without an additional squeeze on profits,
because some of the increased interest expense
would have been offset by lower operating
expenses. And finally, in discussing capital
forbearance policies and portfolio investment
deregulation, it will be seen that insolvent
S&Ls, lacking the proper incentives to control

FEDERAL RESERVE



BANK OF CHICAGO

their risk-taking, should be closed as soon as
possible because they tend to run up substan­
tial losses when left open.
In te re s t-ra te risk

In a world where depository institutions
fund long-term fixed-rate assets with short­
term floating-rate liabilities, unanticipated
increases in interest rates raise costs and put
pressure on profits. This pressure is particu­
larly acute for institutions that have made
long-term loans at fixed rates, the traditional
form of the mortgage contract in the U.S. since
the 1930s. This predicament—interest-rate
risk—is particularly characteristic of the S&L
industry. In periods when short-term interest
rates are expected to rise, S&Ls generate their
greatest interest-rate spreads at the beginning
of life of the mortgage when long-term interest
rates are above short-term interest rates. As
short-term interest rates proceed to rise as
expected, interest-rate spreads decline and
eventually turn negative when short-term
interest rates climb above long-term interest
rates. Likewise, in periods when short-term
interest rates are expected to decline and cur­
rent short-term interest rates exceed current
long-term interest rates, S&Ls experience their
greatest losses. As short-term interest rates
decline, losses are reduced and turned into
gains when short-term interest rates dip below
long-term interest rates.6 During periods of
losses, S&Ls may be said to be experiencing
technical liquidity problems—cash outflows
exceed inflows. Nevertheless, in either case if
their forecasts are correct, the liquidity prob­
lem is only temporary and will not adversely
affect long-term earnings and solvency.
Figure 2 shows that as interest rates
peaked in the early 1980s, the net operating
income of S&Ls plummeted. As interest rates
declined, net operating income improved.
With liabilities repricing more quickly than
assets, sharp and prolonged increases in inter­
est rates can induce long-term losses and en­
danger the solvency of the association. Thus,
a cause of the current S&L crisis is unantici­
pated increases in interest rates.
Judging exposure to interest-rate risk is
difficult because the FHLBB does not release
the data that would allow estimates of the
differences in the durations of assets and lia­
bilities. Given this limitation, exposure must
be inferred from one of two characteristics of

5

FIRREA rescues S&L industry
The Financial Institutions Reform, Recovery
and Enforcement Act of 1989 was signed into
law by President Bush on August 9. It has been
described as landmark legislation that will initiate
wide-ranging changes in the nation’s savings
industry, improve supervisory controls,
strengthen the federal deposit insurance funds,
and bolster public confidence in the savings and
loan S&L industry. Among its major provisions,
the Act:
■Dismantles the Federal Home Loan Bank
Board, transferring all regulatory functions
to the Office of Thrift Supervision, a new
Treasury Department agency.
■Establishes a five-member Federal Housing
Finance Board—composed of the secretary
of the Department of Housing and Urban De­
velopment and four others appointed by the
President with the advice and consent of the
Senate—to oversee the 12 district Federal
Home Loan Banks. These banks can lend to
S&Ls as before and now also to banks and
credit unions that hold at least 10 percent of
their assets in residential mortgages.
■Injects some $50 billion in a new corporation
(Resolution Trust Corporation) to liquidate
or otherwise dispose of institutions that were
once insured by Federal Savings and Loan In­
surance Corporation and which are placed in
conservatorship or receivership in the threeyear period beginning January 1, 1989.

S&Ls. The first is the division of the mort­
gage portfolio between fixed- and adjustablerate instruments. And the second is the inter­
est-rate sensitivity of S&L stock returns.
Table 1 presents data on the composition
of mortgage loan portfolios. This table exam­
ines the portfolio composition of S&Ls nation­
wide and in six states (California, Florida,
Illinois, Louisiana, Oklahoma, and Texas). In
general, both in the nation and in the states
examined, a greater percentage of S&Ls mort­
gages were adjustable-rate instruments at the
end of 1988 than at the end of 1984. In De­

6



■Amends the Bank Holding Company Act to
permit the acquisition of a healthy S&L by a
commercial bank holding company.
■Expands the FDIC Board from three to five
members, including the Comptroller of the
Currency, the Director of the Office of Thrift
Supervision, and three members appointed
by the President, one of whom serves as
chairman.
■Gives the FDIC the responsiblity of manag­
ing a new Savings Association Insurance
Fund (SAIF) and a new Bank Insurance Fund
(BIF).
■Requires each deposit insurance fund to main­
tain reserves of 1.25 percent of estimated in­
sured deposits, or such higher percentage of
estimated insured deposits, not to exceed 1.5
percent, if the FDIC finds that there are sig­
nificant risks of future losses that would
justify a higher ratio.
■Provides the FDIC with greater flexibility to
increase annual deposit insurance premiums
to a maximum of 32.5 basis points.
■Requires banks to pay annual deposit insur­
ance premiums of 12 basis points in 1990 and
15 basis points in 1991. Savings and loan as­
sociations must pay premiums of 23 basis
points in 1991,18 basis points in 1994, and 15
basis points in 1998. The rise in banks’
annual deposit insurance premiums is ex­
pected to generate about $20 billion in addi­
tional premium income over the next 10

cember 1988, adjustable-rate mortgages
(ARMs) accounted for 30 percent or more of
the total mortgages held by about 78 percent
of all FSLIC-insured institutions. In Decem­
ber 1988, the percentage of S&Ls with 30
percent or more of their mortgage portfolio in
ARMs was greater in California, Florida, and
Texas than in the nation as a whole, while in
Illinois, Louisiana, and Oklahoma it was
smaller. From these limited data, S&Ls ap­
peared to be less exposed to interest-rate risk
at the end of 1988 than at the end of 1984.

ECONOMIC PERSPECTIVES

years. Premium income from the S&Ls over
the next 10 years has been estimated to be in
the $25-32 billion range (see Ely [1989]).
■ Requires all S&Ls to maintain tangible capi­
tal of 3 percent on their total assets by the end
of 1994. Purchased mortgage servicing rights—
valued at 90 percent of fair market value—
may be included in capital with the maximum
percentage determined by the FDIC on terms
no less stringent than the FDIC prescribes for
state nonmember banks. Generally the FDIC
allows these rights to account for up to 25
percent of capital.
■Requires S&Ls to raise by July 1, 1991 the
level of housing and housing-related assets in
their portfolio to 70 percent from the current
60 percent. Housing and housing-related as­
sets include core and noncore components.
Core assets must be at least 55 percent of to­
tal assets (and may account for the full 70
percent) They must consist of loans held by
S&Ls to purchase, refinance, construct, re­
pair, or improve domestic residential or manu­
factured housing; home equity loans; mort­
gage-backed securities; and FSLIC, FDIC, or
RTC notes for a limited time (10 years for
current holdings and 5 years for future invest­
ments). Noncore assets are limited to 15 per­
cent of total assets. These assets include 50
percent of residential mortgage loans origi­
nated and sold within 90 days; investments in
service corporations if they derive at least 80
percent of annual gross revenues from activi­
ties directly related to purchasing, refinancing,

The sensitivity of S&L interest margins to
changes in interest rates can be judged by
examining the returns required by the market
for S&L equities. S&L equity returns are
sensitive to all the factors that affect the over­
all stock market as well as to factors specific
to the S&L industry. For example, S&Ls are
sensitive to “earnings risk” through possible
defaults on their loans and investments,
changes in mortgage loan demand, changes in
the value of mortgage loan collateral, and
potential variability in growth and profitability
of their non-portfolio operations. S&L equity

FEDERAL RESERVE



BANK OF CHICAGO

improving, or repairing domestic residential
real estate or manufactured housing; 200 per
cent of the dollar amount of low-income
loans and investments made to acquire 14 family affordable housing, e.g., 60 per
cent of the median value of such housing in a
given geographic area; 200 percent of the
dollar amount of loans for the acquisition or
improvement of residential property, churches,
schools, nursing homes, and small businesses
located in an area servicing the needs of lowand moderate-income families; loans for the
purchase or construction of churches, schools,
nursing homes, and hospitals other than those
listed above; and loans for personal and edu­
cational purposes (up to 5 percent of portfo­
lio assets).
■Restricts the amount of commercial real es­
tate loans to be no more than 400 percent of
the S&L’s capital. In the past, a federal S&L
could devote up to 40 percent of its assets to
such loans, regardless of whether the institu­
tion had any capital.
■Prohibits S&Ls from acquiring or retaining
any corporate debt security that, at the time of
acquisition, is not rated in one of the four
highest rating categories by at least one na­
tionally recognized statistical rating organi­
zation.
■ Prohibits state-chartered S&Ls from acquir­
ing or retaining any equity investment of a
type or in an amount that is not permissible
for federally-chartered S&Ls.

returns are also sensitive to movements in
interest rates because S&Ls typically fail to
match the interest sensitivity of their assets
and their liabilities. As a result, movements in
interest rates affect the market value for each
side of the S&L’s balance sheet, its net worth,
and stock returns.
Brewer (1989) used common stock returns
data to examine the interest-rate sensitivity of
64 S&Ls. The results of this study indicate
that the sampled S&Ls significantly decreased
their interest sensitivity. S&Ls that were mis­
matched in 1984 experienced at least a 70

7

The evidence shows considerable progress in
reducing S&L dependence on FRMs. How­
ever, considering the low level of equity capi­
tal in the industry to absorb losses from unan­
ticipated changes in interest rates, S&Ls con­
tinue to hold too many FRMs.
In te re s t-ra te d e reg u la tio n

percent decrease in their interest-rate sensitiv­
ity over the sample period. Table 2 groups the
sampled S&Ls by the composition of their
mortgage portfolio. In December 1988, a
greater number of S&Ls had more than 30
percent of their mortgage portfolio in adjust­
able-rate mortgages than in December 1984.
The correlation between the change in the
ratio of adjustable-rate mortgages to fixed-rate
mortgages (FRMs) and the change in interestrate sensitivity over the sample period is -0.24
and is significantly different from zero. This
indicates that interest-rate exposure declines as
the proportion of adjustable-rate mortgages
rises.
The findings in this section suggest that
the causes of the initial S&L crisis in the early
1980s were 1) overexposure to interest-rate
risk and 2) high and volatile interest rates.

The Monetary Control Act of 1980 man­
dated the removal of all rate ceilings (these
were specified in the Federal Reserve Board’s
Regulation Q) on consumer-type deposits no
later than 1986. The Gam-St Germain Act of
1982, which authorized the creation of money
market deposit accounts (MMDAs) with lim­
ited transactions features, accelerated progress
toward the final deregulation required by the
Monetary Control Act. Regulation Q was
eliminated for all consumer-type deposits in
March 1986.
Deposit rate ceilings, imposed on com­
mercial banks’ deposits by the Banking Act of
1933, had been extended to the S&L industry
by the Interest Rate Adjustment Act of 1966.
Conventional wisdom had it that deposit-rate
ceilings kept down S&L deposit costs and
were a source of profits to S&Ls. The corol­
lary—that the removal of deposit-rate ceilings
would involve a loss of monopoly profits—
suggests that the recent widespread losses
experienced by the S&L industry are partly
due to the removal of deposit-rate ceilings. It
is argued that the removal of the ceiling has
destroyed the viability of S&Ls in the increas­
ingly competitive market for financial serv­
ices. However, this conventional wisdom
ignores the incentive for S&Ls to compete for
artificially cheap deposits by providing non­
monetary compensation to their depositors.

TABLE 1

Adjustable-rate mortgages (ARMS): FSLIC-insured institutions
(Percent of total mortgages)
Total
industry

Florida

Illinois

Louisiana

Oklahoma

Change in ARMs
(1988-1984)

21.1

27.8

28.0

17.2

8.7

5.4

12.4

The proportion of
institutions at year-end
1988 w ith ARMs over
30 percent

8

California

77.9

93.4

91.7

59.9

68.8

68.4

80.0




ECONOMIC PERSPECTIVES

Texas

TABLE 2

FIGURE 3

Adjustable-rate mortgages:
Sampled stock S&Ls

Some measures of interest rates
percent

Percent

Number of institutions
December 1988
June 1984

0-10

2

14

10-20

6

6

20-30

8

16

30-40

10

11

40-50

10

5

50-60

6

7

Over 60

22

5

Overall

64

64
‘ Estimates obtained from Brewer (1988).

This compensation constitutes “implicit
interest”—payments to depositors in some
form other than cash. One form of implicit
interest is the provision of deposit services—
deposit taking, money orders, statement main­
tenance, and other services—at fees substan­
tially below marginal and average costs. To
attract profitable deposit balances without
paying higher explicit rates, S&Ls also under­
take a range of costly promotional activities,
including advertising, offering gifts to custom­
ers opening new deposit accounts, and provid­
ing increased customer convenience. Estab­
lishing additional branch offices, installing
automated teller machines, and lengthening
operating hours raise S&L expenses, but they
also increase convenience for existing and
potential depositors. Other things the same,
convenience attracts mew S&L depositors.
The true cost of deposits includes the
implicit component as well as the explicit
component. Brewer (1988) used a statistical
cost-accounting technique to estimate the full
cost of S&L regular passbook savings deposits
inclusive of explicit and implicit interest. This
study, using a sample of S&Ls from Illinois
and Wisconsin, shows that under binding inter­
est-rate ceilings, S&Ls have paid implicit rates
of return on savings deposits that move with
the rate on money market mutual funds and 3month T-bills, in periods of both rising and
falling interest rates (see Figure 3). The im­
plicit component of interest rates was highest
in periods when Regulation Q was most bind­
ing. With the removal of binding interest-rate

FEDERAL RESERVE



BANK OF CHICAGO

“ Annual average of the yields on three-month Treasury bills were
constructed from monthly figures. These figures were taken from
various Issues of the Federal Reserve Bulletin. The three-month
yields stated on a discount basis In this source are converted
to bond equivalents.
“ ‘ Annualized total return net of management fees and expenses.
S O URCE: Donoghue’s Money Fund Report of Holllston, Mass.,
various Issues.

ceilings, institutions no longer had an incen­
tive to substitute implicit interest payments, in
the form of increased convenience, service,
and other means of nonprice competition, for
explicit interest. The implications are that
interest-rate deregulation has provided S&Ls
with increased flexibility to compete for funds
using explicit deposit interest rates.
Forbearance policies

Supporters of forbearance policies claim
that S&Ls weakened by technical liquidity
problems should be allowed the chance to
recover. As the temporary problems go away
with declines in interest rates, these S&Ls can
use their new profits to build equity and re­
serves against future losses. But, in recent
years, forbearance has been given to S&Ls
experiencing credit quality problems.
Forbearance programs exempted some
S&Ls from regulatory capital requirements for
extended periods of time. Other S&Ls in
forbearance programs were allowed to invent
assets that artificially inflated their regulatory
net worth. These include nonstandard apprais­
als of equity capital, income capital certifi­
cates, net worth certificates, and deferred
losses. The forbearance program was made
possible in part by advances from Federal
Home Loan Banks. FHLB advances were

9

designed in 1932 to promote industry growth
and to replace lost deposits. Of late, they have
been increasingly used to provide lender-oflast-resort assistance to failing S&Ls that were
losing deposits, particularly uninsured depos­
its. Advances have sometimes been provided
to S&Ls that lacked the necessary collateral in
exchange for a guaranty of repayment pro­
vided by FSLIC.
The lack of reserves in the FSLIC fund
has prevented S&L regulators from closing
those institutions commonly known to be be­
yond hope of recovery. The Competitive
Equality Banking Act of 1987, among other
things, required the Federal Home Loan Bank
Board to give troubled S&Ls time to initiate
strategies that would return them to capital
adequacy. As can be seen in Figure 4, 134 (or
37 percent) of the GAAP-insolvent S&Ls in
December 1988 first reported having negative
TAP capital more than 5 years ago. Similarly,
GAAP reveals that many of the currently in­
solvent S&Ls have been insolvent for quite
some time. In contrast, RAP suggests that the
problem is more recent.7
Analysis of S&L capital in MVA terms, as
shown in Table 3, paints an even grimmer
picture. In December 1988, 674 (or 85 per­
cent) of the 797 market-value-insolvent S&Ls
were also market-value-insolvent in December
1982. The market-value-to-asset ratio for
these institutions at year-end 1982 was -17
percent compared to -13 percent for other
S&Ls that were insolvent in 1982. Therefore,
the least healthy institutions at the end of 1982
proved to be the least healthy at the end of
1988. Accounting measures of net worth also
reveal that these 674 associations had lower
book capital-to-asset ratios than the other
insolvent S&Ls at year-end 1982.
The essence of this analysis is that most of
today’s insolvencies are among those 1982
S&Ls that had the least amount of capital
relative to assets. The conclusion is that for­
bearance was a gamble for the FSLIC, and its
cost has turned out to be significant. The risk
inherent in this gamble comes from the incen­
tive it gave managers to “gamble for resurrec­
tion” by making large volumes of high-risk,
potentially high-profit loans. If the loans
made good, the institutions would have reaped
the profits, but if the loans soured and the
lender went broke, the federal deposit insurer
was liable for the losses, not the institutions’

10



FIGURE 4

Three measures of S&L insolvency*
number of institutions

1

2

3

4

5

6

7

years
‘ Length of insolvency of G AAP- Insolvent FSUC-lnsured
institutions as of Decem ber 3 1 ,1 9 8 6 .

owners. Arising from the combination of
deregulation, inadequate regulatory supervi­
sion, and deposit insurance premiums that are
not based on risk, this incentive to take exces­
sive risks is strongest when there is little eq­
uity left. Thus, it is likely that the magnitude

ECONOMIC PERSPECTIVES

TABLE 3

Market-value-insolvent S&Ls at the end of both 1988 and 1982
(Capital/total assets, expressed as a percent)
Insolvent S&Ls' net worth on December 31,1988
MVA

TAP

GAAP

RAP

-6.0

797 institutions

-1.3

1.5

2.3

S&Ls insolvent on December 31,1988 and December 31,1982
674 institutions

MVA

TAP

GAAP

RAP

1988

1982

1988

1982

1988

1982

1988

1982

-6.0

-17.0

-1.5

-1.5

1.3

-2.4

2.1

3.2

Other insolvent S&Ls at year-end 1982
2,457 institutions

MVA

TAP

GAAP

RAP

-13.1

2.1

3.3

4.0

of the current S&L crisis was made larger by
forbearance policies. The delays in closing
insolvent S&Ls increased the value of access
to deposit insurance and allowed S&Ls to shift
more risk to the deposit insurer.
C re d it ris k and exp an d ed asset po w ers

Whereas problems in the early 1980s were
mainly interest-rate risk related, the problems
in more recent years have been mainly con­
cerned with asset quality. Figure 5 shows a
sharp decline since 1985 in net nonoperating
income, reflecting asset write-downs and addi­
tions to loan-loss reserves. Plunging oil prices
and real estate values in certain regions of the
country have contributed to the sharp deterio­
ration in asset quality of S&Ls nationwide.
Over the 1980-88 period, 488 FSLICinsured S&Ls failed.8 Roughly 160 ( or 30
percent) of failures occurred between 1980 and
1985, which might reasonably be referred to as
the interest-rate risk period. The larger num­
ber of failures over the 1985-88 period is a
consequence, in part, of credit quality prob­
lems. The sharp declines in asset quality
caught some S&Ls at a time when they had
been weakened by interest rate swings.
A major element of risk in holding mort­
gage loans is that the borrower will default or
be delinquent in making mortgage payments.
When a borrower is delinquent on payments,
the S&L incurs a reduction in the return on the
investment. Mortgage actuaries have identi­
fied two major reasons why borrowers default

FEDERAL RESERVE BANK OF CHICAGO




on fixed-rate mortgages (FRMs): insufficient
equity in the property and a burdensome
monthly payment in relation to income. Pay­
ment burden is often the immediate cause of
delinquency. However, if there is substantial
equity in a property, the borrower is more
likely to sell the property and repay the mort­
gage than go to foreclosure. With level-pay­
ment FRMs, changes in borrower payment
burden have been principally due to changes in
income. The experience with FRMs over the
last decade indicates that mortgage balances
declined due to amortization while property
values appreciated, resulting in a growing
equity cushion for the average borrower.
While adjustable-rate mortgages reduce
interest-rate risk for the S&Ls, they may in­
crease credit risk, which can offset part or all
of the reduction in interest-rate risk. Because
ARM periodic payments can increase, a bor­
rower may be unable to sustain the new level
of payments (payment shock). Many ARMs
also include provisions for rising mortgage
balances (negative amortization). When prop­
erty values are appreciating slowly, this provi­
sion may reduce or eliminate the equity cush­
ion. In addition, many lenders have been
using initial rate discounts to encourage bor­
rower acceptance of ARMs. Initial-period
discounts may induce payment shock, particu­
larly if the discount is large and the loan pay­
ment is uncapped. If the discounted loan has a
payment cap, there may be more default risk

11

FIGURE 5

S&L nonoperating income
percent of total assets*

‘ A verage of Individual S&L ratios.

due to the buildup of negative amortization
that occurs early in the life of the loan.
Deregulation has also expanded the menu
of risky assets available to S&Ls. The Mone­
tary Control Act of 1980 allows S&Ls to en­
gage in, among other things, business and
consumer lending. Commercial real estate
lending was restricted to 20 percent of assets,
as were the combined aggregate holdings of
consumer loans, commercial paper, and debt
securities. Additional product lines were de­
regulated by the Gam-St Germain Act of
1982. In particular, the 1982 act relaxed the
quantitative restrictions on commercial real
estate 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 FHLBB permitted federal
S&Ls to invest up to 11 percent of assets in
junk bonds. During the same period, many
state governments enacted statutes that broad­
ened asset powers of state-chartered S&Ls
even more. State-chartered S&Ls were per­
mitted by several states to invest considerable
amounts directly in real estate, corporate equi­
ties, and subsidiary service corporations.
These direct investments have been blamed by
the FHLBB for the losses incurred by the
FSLIC.
Table 4 examines the portfolio composi­
tion of S&Ls nationwide and in each of six
states (California, Florida, Illinois, Louisiana,
Oklahoma, and Texas). In the table, S&Ls are

12




divided into three groups: 1) GAAP insolvent;
2) low capital (that is, positive net worth be­
low 6 percent of assets); and 3) well-capital­
ized S&Ls (with net worth above 6 percent
of assets).
The table shows that there is a substantial
variation among states in the percentage of
assets devoted to direct investments. More­
over, it tends to be the insolvent firms that
engage most prominently in these activities.
Both nationwide and in all six states, insolvent
S&Ls held more direct investments than sol­
vent institutions. At the same time, insolvent
S&Ls held a smaller proportion of their assets
in mortgages (Oklahoma is an exception).
The FHLBB believed that these activities
were increasing S&L risk. In response to the
perceived increase in S&L risk, the FHLBB
took action to restrict S&L investments. On
January 31, 1985, the FHLBB implemented a
regulation, effective March 21, 1985, which
restricted holdings of direct investments (eq­
uity investments in service corporations and
real estate direct investments) by FSLIC-insured S&Ls to the greater of 10 percent of
assets or twice the S&L’s net worth.
Besides nonmortgage investments, capital
forbearance policies may play an important
role in affecting S&L risk. There is evidence
that riskiness varies with the use of financial
leverage.9 How riskiness changes with finan­
cial leverage depends on the regulators’ clo­
sure rule. If equity holders’ position is closed
out when the S&L is found to be insolvent,
then, other things held constant, increases in
financial leverage would be expected to in­
crease risk. This situation raises the probabil­
ity that temporary losses will reduce the
S&L’s net worth below the level needed to
prevent the deposit insurer from closing the
S&L. If the equity holders’ position is not
closed out when the S&L is found to be insol­
vent, then financial leverage increases do not
necessarily imply an increase in risk to equity
holders. In particular, when increases in finan­
cial leverage increase the risk borne by the
deposit insurer, an increase in leverage and
delays in closing insolvent S&Ls may raise the
value of access to deposit insurance and so
lower risk to equity holders. The longer the
delay the greater the effects on risk.
The question is whether these new activi­
ties were in fact riskier. The riskiness of a

ECONOMIC PERSPECTIVES

TABLE 4

Asset composition for all FSLIC-insured institutions
(December 31, 1988)
N e t w o rth
c a te g o ry

Net

C o m m e r c ia l

Consum er

L iq u id

E q u ity

D ir e c t

D e fe r r e d

m o rtg a g e s 1

lo a n s

lo a n s

a s s e ts 2

s e c u r itie s

in v e s t m e n t s

lo s s e s 3

In ta n g ib le
a s s e ts

(P ercen t o f to ta l assets)

61.2

2.6

5.7

12.0

0.2

8.9

1.3

2.5

Between 0 and 6%

68.8

2.9

4.7

13.2

0.3

3.4

0.2

1.8

74.8

1.3

4.0

12.7

0.5

1.8

0.1

1.5

Total industry

in d u s try

Less than or = to 0%

Greater than 6%

T o ta l

69.7

2.5

4,6

13.0

0.3

2.8

0.2

1.8

0.4

Less than or = to 0%

63.2

0.6

0.9

21.3

0.1

6.4

0.2

Between 0 and 6%

74.6

4.2

2.7

10.0

0.1

3.1

0.0

1.1

Greater than 6%

82.1

0.0

1.2

8.5

0.3

1.9

0.0

2.7

Total state

CA

75.4

3.6

2.5

10.0

0.1

3.0

0.0

1.3

Less than or = to 0%

65.3

2.4

8.3

11.2

0.1

6.2

0.6

0.3

Between 0 and 6%

FL

67.2

2.7

6.8

13.7

0.6

2.4

0.2

2.0

Greater than 6%

1.1

4.0

12.1

0.7

2.0

0.0

3.0

68.3

2.4

6.4

13.2

0.6

2.6

0.2

2.1

Less than or = to 0%

69.4

0.4

5.0

14.3

0.0

2.0

3.0

2.1

Between 0 and 6%

IL

74.3

Total state

70.2

0.4

4.0

15.6

0.2

1.4

0.5

3.6

Greater than 6%

13.6

0.3

1.1

0.0

0.5

4.1

14.9

0.2

1.4

0.6

2.3

Less than or = to 0%

61.4

1.8

6.7

9.9

0.2

6.5

1.6

0.7

67.6

0.3

4.1

12.8

1.4

3.9

0.5

6.1

68.1

0.2

5.9

8.5

0.2

11.6

0.1

3.1

Total state

66.1

0.7

5.4

10.7

0.7

7.0

0.7

3.7

Less than or = to 0%

67.3

0.5

9.3

7.6

0.4

10.7

0.3

0.0

Between 0 and 6%

61.9

1.3

4.3

20.6

0.2

6.9

0.0

1.4

Greater than 6%

45.7

0.7

2.6

23.8

1.9

9.9

-0.0

8.4

Total state

59.2

1.1

4.4

20.1

0.6

7.8

0.0

2.6

Less than or = to 0%

51.0

3.3

3.4

11.3

0.1

19.4

0.2

4.4

Between 0 and 6%

46.5

2.1

2.5

24.1

0.1

15.6

0.2

1.6

Greater than 6%

53.5

1.3

8.4

21.6

0.7

5.2

0.1

2.8

Total state

TX

3.9

0.4

Greater than 6%

OK

0.4

72.1

Between 0 and 6%

LA

73.1

Total state

48.2

2.4

3.0

20.0

0.1

16.4

0.2

2.5

’Mortgage loans, contracts, and pass-through securities net of contra-assets.
2Cash and investment securities (excluding equity securities).
Negative amount indicator deferred gains.

portfolio—that is, the variance in the return on
the entire set of assets held by an S&L—can
decrease when relatively risky assets are
added. Portfolio riskiness depends on the
covariance among assets. For example, if the
returns on a relatively risky asset tend to be
high when the returns on other assets are low,
i.e., negative covariance, adding the relatively
risky asset will reduce the overall riskiness of
a portfolio.

FEDERAL RESERVE



BANK OF CHICAGO

One method of assessing the effect of
nonmortgage investments on S&L risk is to
examine the results of diversification efforts
by S&Ls since the Monetary Control Act of
1980. Benston (1985) used accounting data to
measure the relationship between risk (defined
as the standard deviation of accounting re­
turns) and S&Ls’ direct investments. Data
were analyzed for the three years ended June

13

30, 1984 for all S&Ls in the nation and in
states with liberal direct investment regula­
tions. Direct investments as a percentage of
assets were found to be slightly negatively
related to risk. But, a study by the FHLBB in
1984 reported that many S&Ls had diversified
into direct investment in ways that increased,
rather than diminished, their exposure to risk.
Among other things, the FHLBB reported that
S&Ls with significant direct investments in
service corporations or real estate hold asset
portfolios with significantly more credit risk.1
0
A more recent study by Benston and Koehn
(1989) used stock market data for the July
1978-December 1985 period to discern the
impact of nonmortgage investments on S&L
risk. Using the standard deviation of equity
returns as a measure of risk, they found that
direct investments tend to reduce risk, except
at S&Ls with low capital. Direct investments
at low capital S&Ls are significantly posi­
tively related to risk. Nontraditional loans do
not appear to be significantly associated
with risk.
Recent work by Brewer (1989) supports
the findings of Benston and Koehn. He re­
gressed the standard deviation of equity re­
turns for a sample of 64 S&Ls on the ratios to
market value of equity of total deposits; of
traditional fixed-rate mortgage loans; of ad­
justable-rate mortgage loans; of direct invest­
ments; of nonmortgage loans; and of FHLB
advances. Dummy variables on financial lev­
erage are included in the model to capture the
impact of delay in closing insolvent S&Ls on
risk.1 The differential behavior of high-risk
1
S&Ls compared to low-risk S&Ls was ana­
lyzed. For high-risk S&Ls the findings indi­
cate that direct investments and nonmortgage
loans have a strong and consistent positive cor­
relation with risk. Adjustable-rate mortgages
at high-risk S&Ls are significantly positively
related to risk, supporting concerns of many
that the credit risk of these instruments is sig­
nificant. Traditional fixed-rate mortgages do
not appear to be statistically correlated with
risk. The findings for the low-risk category
indicate little evidence of a statistically signifi­
cant association between nonmortgage activi­
ties and S&L risk. In addition, the results
suggest that for insolvent S&Ls operating
under capital forbearance, financial leverage
has less of an impact on risk than for solvent

14




firms. This occurs because risk-taking is being
subsidized more for insolvent S&Ls than for
solvent associations.
While these findings raise concern about
asset deregulation, they are also consistent
with the view that high-risk S&Ls are using
both mortgage and nonmortgage assets to take
even greater risks because they lack the proper
incentives to control their risk-taking. Reregu­
lation of investments made by high-risk S&Ls
would not affect their risk preferences. The
preceding discussion suggests, however, that
more timely closure and meaningfully en­
forced capital requirements can be effective in
providing the proper incentives for S&Ls to
control their risk-taking.
R eform le g islatio n

The S&L crisis suggests that piecemeal
efforts to introduce financial reforms, coupled
with policy efforts that focus on the symptoms
of the financial problems rather than on their
underlying causes, have contributed to, rather
than diminished, unstable financial conditions
in this country. In particular, legislative
changes that have weakened constraints on
risk-taking by federally insured S&Ls, without
introducing changes to the nation’s system of
financial safety nets, have contributed to cur­
rent financial difficulties.
The Financial Institutions Reform, Recov­
ery and Enforcement Act of 1989 addresses
some but not all of the problems faced by the
S&L industry. The act is designed to restruc­
ture the way the S&L industry is regulated and
insured, improve supervisory control, and
dispose of all currently insolvent S&Ls. The
lack of reserves in the FSLIC fund has pre­
vented S&L regulators from closing those
institutions commonly known to be beyond
hope of recovery. FIRREA injects funds into a
new corporation designed to resolve currently
insolvent S&Ls in an orderly fashion. At best,
the total cash outlays authorized by FIRREA
will allow regulators to close currently insol­
vent S&Ls that are running up losses and dis­
torting the deposit-taking and lending markets.
However, the new legislation, like the Com­
petitive Equality Banking Act of 1987, does
not provide for sufficient funds to handle po­
tentially large future insolvencies.
The act deals with the lack of tangible
capital in the industry by requiring all S&Ls to

ECONOMIC PERSPECTIVES

satisfy a tougher capital standard by the end of
1994. Additional capital can reduce the expo­
sure of the federal deposit insurance fund to
S&L losses. In addition, increased capital
requirements probably reduce an S&L’s incen­
tive to expand asset risk and thereby increase
the risk of loss to the deposit insurance fund.
The empirical results of this article support
this point.
But, although the act requires S&Ls to
maintain minimum capital standards, it does
not provide for early closure and mark-tomarket accounting for evaluating S&L capital
positions. The importance of measuring capi­
tal in market-value terms rather than in bookvalue terms is demonstrated by the results of
this article.1 The evidence reported here indi­
2
cates that, while book value of capital was
positive throughout the 1980s, the market
value of capital was negative, reaching a low
of about -$100 billion in 1982. There are
difficulties in implementing a mark-to-market
accounting approach to capital, particularly the
problem of providing an accurate assessment
of the values of assets that do not have
broadly-based markets in which they are
traded. Nevertheless, mark-to-market account­
ing has the singular advantage of making the
managers of S&Ls more immediately account­
able for their portfolio decisions. It will also
eliminate the elements of forbearance implicit
in current accounting standards that allow
some institutions to carry assets at book value
until those assets are removed from their bal­
ance sheet.
Another, equally important, change from
current regulatory practices that should have
been included in FIRREA was omitted. This
is a requirement that all S&Ls, regardless of
region of the country or size, that are deter­
mined to have insufficient capital must be
closed, recapitalized, or otherwise restructured
along the lines suggested by Benston and
Kauffman (1988).
FIRREA places excessive reliance on the
regulatory mechanism to prevent a recurrence
of the S&L crisis. However, the federal gov­
ernment simply cannot substitute for market
oversight in controlling risk. The federal regu­
latory agencies will never have the personnel
or the financial resources to effectively regu­
late a financial system as large and diverse as
ours. Adequate oversight requires not only
having interested parties who are in a position

FEDERAL RESERVE



BANK OF CHICAGO

to monitor managerial behavior on a regular
basis, but also an environment in which the
attention of depository managers is focused on
making decisions that emphasize financial
stability and health first.
FIRREA restricts the ability of S&Ls to
make and hold nonmortgage assets and re­
quires S&Ls to raise the level of housing and
housing-related loans in their portfolio to 70
percent from the current 60 percent level. The
events of the early 1980s provide evidence that
such portfolio restrictions expose depository
institutions to both interest-rate and credit
risks. The evidence presented in this article
suggests that high-risk S&Ls tend to take ex­
cessive risks of all types (both in mortgage and
nonmortgage investments). Therefore, deregu­
lation may have made it easier for high-risk
S&Ls to take excessive risks, but it also re­
duced the risk at well-managed S&Ls. The
portfolio restrictions included in FIRREA will
reduce the ability of S&Ls to engage in riskreducing diversification. In addition, this
research indicates that reregulation of invest­
ments made by S&Ls would not affect their
risk preferences. Risky portfolios can also be
assembled with housing and housing-related
loans.
W h a t rem ains to be done

The existing regulatory structure creates
incentives for S&Ls to hold risky portfolios.
Under the current structure, depositors do not
have any incentive to impose market discipline
on the use of their funds because the deposits
are insured. The current system allows S&Ls
to use depositors’ funds to engage in riskier
activities than would otherwise be possible.
This distortion in the existing regulatory struc­
ture can be eliminated by creating a class of
creditors that is specifically available to moni­
tor S&L risk and bear the risk of loss. An
essential element in the recent Federal Reserve
Bank of Chicago proposal (see Keehn [1989])
for restructuring the financial services industry
is the requirement that depository institutions
maintain a specified level of subordinated debt
relative to their risk-adjusted assets. Like
equity, the debt would serve as a cushion to
depositors and the deposit insurance fund.
However, the debt, properly structured, would
also facilitate the imposition of market disci­
pline on management of depository institu­

15

tions, prevent debtholders from “running”
when the institution encountered financial
difficulties, eliminate pressures for systemic
bank runs, and provide for orderly closure,
recapitalization, or other types of restructuring.
Policies that reduce this type of market
discipline will certainly create incentives for
S&Ls to take risks. The S&L crisis has re­
vealed a fundamental problem in our system
for supervising depository institutions. De­

spite its strengths, the Financial Institutions
Reform, Recovery and Enforcement Act of
1989 does not address all of the problems of
the S&L industry. It is important to remember
that politically sponsored forbearance and lax
supervision by themselves would probably not
have created a crisis of the current magnitude.
By distorting the market for depositors, the
existing system of deposit insurance aided,
abetted, and augmented the disaster.

FOO TNOTES
'See BertO. Ely (1989).
2Current market values of assets and liabilities can also
differ from their historical values because of changes in the
value o f loan collateral, or in the riskiness of unsecured
loans.
3Goodwill consists principally of the amount over book
value paid by an S&L to acquire other S&Ls.

to old mortgage rates, homeowners have an incentive to
refinance mortgage balances at a lower rate. As a result,
S&Ls’ potential portfolio gains from falling market interest
rates are limited by prepayments.
7See Barth, Bartholomew, and Labich (1989) for a similar
analysis.
8Failed S&Ls are those closed or merged with FSLIC
assistance.

4By comparison, this amount is similar to that reported by
Kane in his 1985 monograph.

9See Ang, Peterson, and Peterson (1985).

5See Barth, Bartholomew, and Labich (1989).

10See Federal Home Loan Bank Board (1984), p. 47862.

6However, the presence of prepayment options tends to
hamper the ability of S&Ls to adjust their mortgage yields
during periods o f declining interest rates. Homeowners
have the option to pay the balance of their mortgages at any
time. Other than predetermined schedules of prepayment
penalties, S&Ls have no control over homeowners’ prepay­
ment decisions. When new mortgage rates decline relative

n Brickley and James (1986) found that as the FHLBB
relaxed insolvency rules, thereby shifting more risk to the
FSLIC, the systematic risk of S&Ls fell.
,2See Benston and Kaufman (1988) and White (1989) for a
discussion of the importance of measuring capital in mar­
ket-value terms.

REFERENCES

Ang, James, Pamela Peterson, and David
Peterson, “Investigations into the Determi­
nants of Risk: A New Look,” Quarterly Jour­
nal of Business and Economics, vol. 24, Win­
ter 1985, pp. 3-20.

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 Bothers Center for
the Study of Financial Institutions, 1988.

Barth, James R., Philip F. Bartholomew,
and Carol Labich, “Moral Hazard and the
Thrift Crisis: An Analysis of 1988
Resolutions,” Proceedings of a Conference on
Bank Structure and Competition, Federal Re­
serve Bank of Chicago, 1989.

Benston, George J., An Analysis of the
Causes of Savings and Loan Association Fail­
ure, Monograph Series in Finance and Eco­
nomics, Salomon Bothers Center for the Study
of Financial Institutions, 1985.

Benston, George J., and Michael F. Koehn,
“Capital Dissipation, Deregulation, and the
Insolvency of Thrifts,” Unpublished paper,
June 1989.

Brewer III, Elijah, “Risk, Regulation, and
S&L Nonmortage Investments,” Federal Re­
serve Bank of Chicago, Working Paper (in
press), 1989.

16

ECONOMIC PERSPECTIVES




Brewer I I I , Elijah, “Interest-Rate Risk Re­
duction in S&L Portfolios Through Adjust­
able-Rate Mortgages,” Federal Reserve Bank
of Chicago, Working Paper (in press), 1989.
Brewer I I I , Elijah, “The Impact of Deregula­
tion on the True Cost of Savings Deposits:
Evidence from Illinois and Wisconsin Savings
and Loan Associations,” Journal of Economics
and Business, Vol. 40, February 1988, pp.
79-95.
Brickley, James A., and Christopher M.
James, “Access to Deposit Insurance, Insol­
vency Rules and the Stock Returns of Finan­
cial Institutions,” Journal of Financial Eco­
nomics, Vol 16, July 1986, pp. 345-371.
Ely, Bert O., Statement before the Committee
on Banking, Finance, and Urban Affairs, U.S.
House of Representatives, “Financing the S&L
Rescue Package”, Hearing, 101st Congress, 1st
Session, June 1, 1989, pp. 95-113.

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.
Kane, Edward J., The Gathering Crisis in
Federal Deposit Insurance, MIT Press, Cam­
bridge, MA, 1985.
Keehn, Silas, Banking on the Balance Powers
and the Safety Net: A Proposal, Federal Re­
serve Bank of Chicago, 1989.
U.S. Congress, House of Representatives,
Financing the S&L Rescue Package, Hearing,
101st Congress, 1st Session, June 1, 1989,
Washington: G.P.O., 1989.
White, Lawrence J., “The Reform of Federal
Deposit Insurance,” Proceedings of a Confer­
ence on Bank Structure and Competition,
Federal Reserve Bank of Chicago, 1989.

INDEX
ECONOMIC PERSPECTIVES— Index for 1989
Pages

Economic conditions

Issue

Pages

Banking, credit, and finance

Issue

Deposit insurance:
Lessons from the record

May/Jun 10-30

Capacity utilization and inflation May/Jun 2-9
The geography of value added
Sep/Oct 2-12

Banking 1988:
The eye of the storm

Jul/Aug 2-12

Public investment and productivity
growth in the Group of Seven
Sep/Oct 17-25

continued

25th Conference on Bank Structure
and Competition: Controlling risk
in financial services
Sep/Oct 13-16

Investment cyclicality in
manufacturing industries

Full-blown crisis,
half-measure cure

Money and monetary policy

Nov/Dec 2-17

Nov/Dec 19-28

Reconsidering the regional
manufacturing indexes

Jul/Aug 13-21

Hostile takeovers and the market
for corporate control
Jan/Feb 2-16

Testing the “ spread”

Jul/Aug 22-33

Countertrade—
counterproductive?

Jan/Feb

Unemployment insurance and
regional economic development

Mar/Apr 2-15

To order copies of any of these issues, or to receive
a list of other publications, please write to: Federal
Reserve Bank of Chicago, Public Information
Center, P. O. Box 834, Chicago, IL 60690-0834, or
telephone (312) 322-5 111.

Economic conditions

17-24

Competitive pricing behavior in
the U.S. steel industry
Mar/Apr 16-26

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17

Call for Papers

The 26th annual Conference on Bank
Structure and Competition
Chicago, Illinois, May 9 -11,1990

The Conference will also feature a discus­
sion and critique of the Financial Institutions
Reform, Recovery, and Enforcement Act of
1989 and the current status of the program to

The Federal Reserve Bank of Chicago will

restructure the thrift industry. We are seeking

hold its 26th annual Conference on Bank

papers on these topics as well as on other

Structure and Competition in Chicago, Illinois,

issues related to the structure and regulation

May 9-11,1990.

of the financial services industry.

The Conference has become a nationally

If you or any of your colleagues wish to

recognized forum for the exchange of ideas

present a paper at the Conference, please

among academics, regulators, and industry

submit two copies of your completed paper or

participants with a strong interest in public

abstract by December 31,1989, to: Conference

policy toward the financial services industry.

on Bank Structure and Competition, Research

This year's Conference will focus on the in­

Department, Federal Reserve Bank of Chicago,

creasing competitiveness of the financial

230 South LaSalle Street, Chicago, Illinois

services industry and its implications for regu­

60604-1413. For additional information, call

latory policy and bank management. Topics

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include interstate banking, globalization of

(312/322-6199).

financial markets, expanded banking powers,
new products, and competition from capital
markets and from nonbank financial firms.

18




FEDERAL RESERVE BANK
OF CHICAGO

ECONOMIC PERSPECTIVES

In v estm e n t c y c lic a lit y in
m a n u fa c tu rin g in d u s trie s

Industrial investment tracks the business
cycle, in general; but, when you get down to
particulars, the picture is more complicated
and, for analysts, more meaningful

Bruce C. Petersen
and W illiam A . Strauss

It is well known that invest­
ment fluctuates proportion­
ately by much more than total
output. The evidence on this
is quite dramatic. Consider
for example the ratio of net investment to GNP
over the period 1946 to 1985. The lowest
values of this ratio all occurred during reces­
sion years; while the mean of the ratio was 5.6
percent, the ratio was 2.9 percent in 1982, 3.3
percent in 1975, 3.7 percent in 1983, and 4.0
percent in 1976. In contrast, the ratio tends to
be high in boom periods.'
In addition, investment closely tracks the
business cycle. This procyclicality of invest­
ment is extremely important in accounting for
the “shortfall” of GNP during downturns in the
economy. Robert Barro’s calculation of the
difference between actual GNP and a smoothly
growing “potential” GNP series over the pe­
riod 1946 to 1985 shows that if all categories
of investment are added together, fluctuations
in investment account for 88 percent of the
GNP shortfall during recessions. Barro con­
cludes that “as a first approximation, explain­
ing recessions amounts to explaining the sharp
contractions in the investment components.”2
There are many competing views explain­
ing why investment is so procyclical. Among
the most widely known hypotheses are the
accelerator model; the neoclassical investment
model, emphasizing the cost of capital and
stock adjustments; and the cash flow model
under conditions of imperfect capital markets.
To date, there is no widespread agreement on

FEDERAL RESERVE



BANK OF CHICAGO

which view of investment is most consistent
with the facts concerning the cyclicality of
investment.
In this article, we do not directly test any
of the competing theories of investment.
Rather, we explore the cyclicality of fixed
investment at the industry level within the
manufacturing sector. Very little attention has
been given to examining investment at this
level. The lack of information about industry
behavior is probably due to the fact that in­
vestment studies employing firm data typically
do not have enough data points to produce
estimates of cyclicality across a wide range of
industries.
There are some very basic questions con­
cerning industry investment behavior that must
be addressed. Do all broadly defined indus­
tries exhibit roughly the same degree of invest­
ment cyclicality over the business cycle? If
not, is there some obvious pattern in the data
that permits a useful organization of industries
according to their degree of cyclicality? There
is no obvious pattern in cyclicality predicted
by investment models that focus only on the
cost of capital. On the other hand, if industries
do exhibit different investment patterns over
the business cycle, then theories emphasizing
either firm- or industry-specific determinants
of investment may be required.
Bruce C. Petersen and W illiam A. Strauss are
economists at the Federal Reserve Bank of Chicago.
The authors thank Charles Him m elberg, Ed Nash,
and Steve Strongin fo r comments.

19

To investigate industry cyclicality, we use
a panel of 270 industries at the four-digit Stan­
dard Industrial Classification (SIC) level for
the time period 1958 to 1986. For most of the
issues explored in this study, we aggregate this
panel to the two-digit SIC level of disaggrega­
tion. We find that most of the 20 two-digit
industries do exhibit procyclical investment
behavior over the period of our study. There
are, however, marked differences across these
industries both with respect to investment
volatility and to investment cyclicality. Indus­
tries such as food products exhibit little or no
investment cyclicality. Our main finding is
that industries producing non-durable goods
exhibit less cyclicality in investment than
industries producing durable goods. Very
often the difference is quite striking.
The remainder of the article proceeds as
follows: The next section briefly reviews
alternative views of investment cyclicality and
some of the existing evidence. The-following
section describes the panel database employed
in the study and the method used to construct
“smoothed” industry investment series. Fi­
nally, we report our results on both the volatil­
ity and cyclicality of industry investment.
T h eo ries o f in v e s tm e n t c y c lic a lity

There are a number of investment theories
that predict that investment should be a vola­
tile component of GNP. Space permits only a
cursory overview of three of the leading con­
tenders; we describe here the predictions of
the accelerator model, the neoclassical model,
and the cash flow model.3
The accelerator model hypothesizes that
the level of net investment depends on the
change in expected demand for business out­
put. According to this theory, a business’s
desired stock of capital varies directly with its
level of output. Thus, when there is an “accel­
eration” in the economy and expected output
increases, net investment is positive. The
opposite occurs when there is a deceleration
and net investment can actually become nega­
tive. Depending on the size of the capitaloutput ratio, investment can be several times
more volatile and procyclical than output.
Neoclassical models have a theoretical
advantage over the simple accelerator model
in that they include the cost of capital as one
of the determinants of the desired stock of
capital and thus the level of investment. Some

20



economists explain the volatility of investment
through the cost-of-capital channel.4 Their
argument is essentially that when the real rate
of interest changes, all firms experience a
change in their desired stock of capital. Given
that any year’s investment amounts to a small
portion of the total capital stock, even a rela­
tively small percentage change in the desired
stock of capital can result in large percentage
changes in net investment. Shocks to the real
interest rate can cause firm investment to be
very volatile and industry investment to be
procyclical.
The cash flow model also has a long tradi­
tion in the investment literature. In a world of
perfect capital markets, sources of finance are
irrelevant for the investment decision. How­
ever, when there are imperfections in capital
markets, then internal finance generally has a
cost advantage over external finance. When
this is true, then sources of finance do matter.
In particular, the quantity of internal finance,
or cash flow, should be positively associated
with the level of investment. Since firm prof­
its and cash flows are very procyclical, the
cash flow model of investment also predicts
that investment will be procyclical. Further­
more, it predicts that investment will be more
procyclical for industries which experience the
most procyclicality in profits.
Evidence on th e c y c lic a lity o f
in v es tm e n t

There is no widespread agreement on
which of these theories is most consistent with
the facts concerning the cyclicality of invest­
ment. Over the last three decades, a large
number of empirical studies have been under­
taken, many of them with firm data. An excel­
lent review of the literature before 1970 can be
found in Kuh (1971). A review of some of the
more recent literature can be found in Fazzari,
Hubbard, and Petersen (1988).
Many of the earlier empirical studies such
as Kuh (1971), Meyer and Kuh (1957), and
Meyer and Glauber (1964) focused on accel­
erator and cash flow models of investment,
typically finding some support for both expla­
nations. In the last two decades, however,
empirical research has shifted toward neoclas­
sical models of investment. The impetus for
this shift in direction came from the influential
work of Modigliani and Miller (1958) who
demonstrated that under certain conditions,

ECONOMIC PERSPECTIVES

real investment decisions can be separated
from purely financial factors; that is, that fi­
nancial factors such as cash flow may be ir­
relevant to investment decisions. Whether this
separation of real investment from financial
considerations exists in practice is still being
debated.5
A review of the empirical literature on the
determinants of investment reveals that almost
no studies systematically consider investment
behavior at the industry level. Studies typi­
cally use either aggregate investment series for
the whole economy or a sector of the economy
or they use firm data. Firm data has many
advantages over aggregate data for examining
economic behavior. However, most studies
that employ firm data do not have enough data
points to permit estimates of differences in
investment behavior across industries. This is
probably the explanation for the paucity of
studies that compare the investment behavior
of a large number of industries for a substan­
tial time period.
There are, however, some potentially
interesting facts that can be learned by exam­
ining investment behavior at the industry level.
It is well known that industries, even within
manufacturing, do not respond alike to the
business cycle. For example, some industries,
such as those engaged in the processing of
food, experience very little variation in de­
mand for their output over the cycle. On the
other hand, industries that produce durable
goods experience considerable variation in
demand and cash flow.
This raises an interesting test of models of
business investment. Models which emphasize
only the cost of capital do not predict system­
atic differences in investment cyclicality
across industries. However, both the cash flow
and the accelerator models clearly do. In the
following sections of this article, we seek to
set out some of the facts about differences in
investment behavior at the industry level.
The d ata

The primary data sources utilized in this
study are the Census of Manufactures and the
Annual Survey of Manufactures (U.S. Bureau
of the Census). There are several reasons why
these data sources are the best available for
examining the cyclicality of investment at the
industry level. First, the Census reports invest­
ment data at the four-digit level, which is very

FEDERAL RESERVE



BANK OF CHICAGO

disaggregated. Second, Census data assign
individual plants, rather than whole compa­
nies, to their primary SIC industry. Since
plants are typically much more specialized
than companies, the problem of contamination
is negligible. Finally, the data for most Cen­
sus industries are available back to at least
1958, allowing for a panel of substantial
length.
The Census of Manufactures currently
contains approximately 455 four-digit indus­
tries, of which 270 are included in our panel.
Since, it is either impossible or inconvenient to
work with the entire population of Census
industries, we excluded industries for any of
three reasons. First, because we wished to
examine a balanced panel of industries cover­
ing as many business cycles as possible, we
excluded all industries for which the Census of
Manufactures began gathering data later than
1958. Second, we excluded a number of in­
dustries having large gaps in the data. Finally,
we excluded industries with inconsistencies in
the industry classification or definition over
time.6
Table 1 provides a summary of the break­
down of our sample of Census industries
across the 20 two-digit manufacturing indus­
tries. The first column lists the identity of the
20 industries that make up the Census of
Manufactures. The second column lists the
total number of four-digit industries which
made up each of the two-digit Census indus­
tries in 1986. The third column reports the
breakdown of our sample of industries across
the two-digit industries. The fourth column
indicates the percentage of four-digit indus­
tries contained in our database. The fifth and
sixth columns state what the average real in­
vestment (1982 dollars) was for each two-digit
industry both for the Census population and
our sample of four-digit industries.7 The final
column indicates the percentage of real invest­
ment accounted for by our set of industries.
It can be easily ascertained from Table 1
that our sample contains some 59.3 percent of
the total number of four-digit industries cur­
rently contained in the Census. This percent­
age varies across two-digit industries, the low
being 25.3 percent in SIC 24. Our coverage of
total manufacturing investment is considerably
higher; over the 1958-1986 period, our sample
includes 77.1 percent of all investment.

21

TABLE 1

FRB data base analysis: 1958 to 1986 real investment
T o ta l n u m b e r

FRB d a ta b a se ,

o f fo u r d ig it
in d u s tr ie s

SIC 20 - Food and kindred products
SIC 21 - Tobacco products

d id g e t in d u s tr ie s in

P e rc e n t

a v e ra g e

a v e ra g e

P e rc e n t

in 1 9 8 6

T o t a l m a n u f a c t u r in g

N u m b e r o f fo u r -

1 9 5 8 -1 9 8 6

1 9 5 8 -1 9 8 6

FR B d a ta b a s e

o f to ta l

in v e s tm e n t

in v e s tm e n t

o f to ta l

5 9 .3

5 7 ,4 5 3 .6

4 4 ,3 2 2 .1

455

270

7 7 .1

47

38

80.9

5,124.1

4,463.2

87.1

4

4

100.0

314.9

314.9

100.0
79.7

SIC 22 - Textile mill products

30

19

63.3

1,726.6

1,375.3

SIC 23 - Apparel and related products

33

15

45.5

602.8

305.0

50.6

SIC 24 - Lumber and wood products

17

4

23.5

1,618.5

984.7

60.8

SIC 25 - Furniture and fixtures

13

7

53.8

521.1

258.1

49.5

SIC 26 - Paper and allied products

17

11

64.7

3,938.3

3,602.9

91.5
57.1

SIC 27 - Printing and publishing

17

8

47.1

2,363.2

1,348.8

SIC 28 - Chemicals and allied products

33

16

48.5

7,625.1

4,585.7

60.1

6

5

83.3

2,994.3

2,994.3

100.0

SIC 29 - Petroleum and coal products
SIC 30 - Rubber & plastic products
SIC 31 - Leather and leather products

6

4

66.7

1,992.1

1,705.4

85.6

11

3

27.3

142.7

47.4

33.2

SIC 32 - Stone, clay and glass products

27

23

85.2

2,389.5

2,281.8

95.5

SIC 33 - Primary metal industries

26

18

69.2

5,736.6

5,097.7

88.9
64.0

SIC 34 - Fabricated metal products

36

19

52.8

3,076.3

1,970.2

SIC 35 - Machinery, except electrical

44

29

65.9

5,287.8

4,187.1

79.2

SIC 36 - Electrical machinery

37

25

67.6

4,522.3

2,848.8

63.0

SIC 37 - Transportation equipment

18

8

44.4

5,607.5

4,919.5

87.7

SIC 38 - Instruments & related products

13

7

53.8

1,256.5

895.2

71.2

SIC 39 - Miscellaneous manufacturing

20

7

35.0

613.4

136.1

22.2

Again, this percentage varies somewhat across
the two-digit categories.

smoothing” procedure, is given in the equation
below:
t+ ^1

C o n s tru c tin g th e s m o oth ed
in v e s tm e n t series

To examine investment cyclicality, we are
going to compare in the next section each
industry’s actual investment series to a
“smoothed” investment series, where the
smoothed investment series is the average of
recent investment levels. The logic of our ap­
proach is quite straightforward. If an indus­
try’s actual investment tends to be above its
smoothed investment series in boom times and
below during economic contractions then
actual investment is clearly procyclical. The
degree of cyclicality is measured by the extent
to which actual investment deviates from
“smoothed” investment during economic ex­
pansions and contractions.
For comparison, we indexed the actual
(deflated) investment for all two-digit indus­
tries, setting the value in 1958 at 100. To
construct the smoothed investment series, we
chose the simplest possible technique that
would accomplish our objective. The method
used, known as a “centered moving average

22



')

l'
~=l

X

/,

i=t-ts=H
2

where / is actual indexed investment in
year t; / is the smoothed value of indexed
investment in year t; and n is the number of
years over which investment is averaged.8 We
experimented with alternative values for n,
settling on a value of nine as a compromise for
achieving the twin goals of producing a
smoothed investment series which also re­
sponds reasonably quickly to changes in the
growth rate or trend in industry investment.9
Graphs of the actual and smoothed invest­
ment series appear below for all manufacturing
and selected two-digit industries. Figure 1
plots the investment series for all manufactur­
ing over the time period 1958-1986. The ac­
tual investment series is indicated by the black
line while the smoothed series is indicated by
the color line. Figures 2-5 report the same
information for selected two-digit industries.

ECONOMIC PERSPECTIVES

Figures 2-5 all have the same vertical scale to
facilitate cross-industry comparisons. The
industries are as follows: food and kindred
products (SIC 20); chemicals and allied prod­
ucts (SIC 28); industrial machinery and equip­
ment (SIC 35); and transportation equipment
(SIC 37). These industries have a large share
of total investment in manufacturing, and as
will become apparent, they illustrate different
types of industry investment behavior.1
0
An inspection of Figures 1-5 below indi­
cates that the procedure outlined in Equation
(1) appears to do a satisfactory job of creating
a smoothed investment series for each indus­
try. To see this, compare the actual invest­
ment series for each industry with its smoothed
investment series. The smoothed investment
series picks up the trend in each industry’s
investment series without being unduly af­
fected by the fluctuations in the actual invest­
ment series around its trend.
In Figures 1-5, the differences between
the actual investment series (black line) and
the smoothed investment series (color line) il­
lustrate the cyclical behavior of industrial
investment. In Figure 1, for total manufactur­
ing, the peaks and valleys in investment over
the business cycles between 1958 and 1986 are
quite evident. In addition, an inspection of
Figures 2-5 indicates that there is a wide range
of cyclical investment behavior for SIC 20, 28,
35, and 37.

FEDERAL RESERVE



BANK OF CHICAGO

TABLE 2

Coefficient of variation of
the investment ratio
Coefficient
of variation
Total manufacturing
SIC 20 - Food and kindred products

9.9
4.8

SIC 21 - T obacco products

22.2

SIC 22 - Textile m ill products

14.2

SIC 23 - A pparel and related products

11.7

SIC 24 - Lum ber and w o o d products

18.0

SIC 25 - Furniture and fixtures

15.7

SIC 26 - Paper and allied products

13.3

SIC 27 - Printing and p ub lishing

11.3

SIC 28 - C h em icals and allied products

12.9

SIC 29 - Petroleum and coal products

22.5

SIC 30 - Rubber and plastic products

18.0

SIC 31 - Leather and leather products

22.2

SIC 32 - Stone, clay and glass products

14.7

SIC 33 - Prim ary metal industries

18.1

SIC 34 - Fabricated metal products

11.8

SIC 35 - M achinery, except electrical

13.6

SIC 36 - Electrical m achinery

12.3

SIC 37 - Transportation equipm ent

23.2

SIC 38 - Instruments and related products

16.2

SIC 39 - M iscellane ou s m anufacturing

12.5

V o la tility o f in d u stry in v e s tm e n t

Before turning to the statistical results on
the cyclicality of industry investment, it is of
interest to report the differences in the volatil­
ity of industry investment. It is quite apparent
from Figures 2-5 that some indus­
tries exhibit more volatile invest­
ment than others. To quantify this,
we form the ratio of actual to
smoothed investment ( / / 7 ) for
each year for each industry and
compute the coefficient of vari­
ation, reported in Table 2.1
1
Judging by the size of the co­
efficients, the industry with the
most volatile investment series is
the transportation industry (SIC
37), closely followed by the petro­
leum (SIC 29) and tobacco (SIC
21) industries. At the other end of
the scale, the food industry (SIC
20) has a coefficient of variation
about five times smaller than that
of the transportation industry.
When volatility is measured by

23

The c y c lic a lity o f in d u stry
in v e s tm e n t

We turn now to the descriptive
statistics on the cyclicality of in­
dustry investment. We fit the fol­
lowing relationship to each indus­
try’s investment series:
2)

1
— = a + bA

+€
M

FIGURE 3

Indexed real investment
(SIC 28: Chemicals and allied products)
index, 1958=100

output or sales, it is well known that transpor­
tation is one of the most volatile industries and
that food is one of the least volatile industries.
It is apparent from Table 2 that this is also true
with respect to their investment.
But, high volatility is not necessarily
linked to high cyclicality, as we shall see in
the next section. While the two conditions are
linked in the case of the transportation indus­
try, they definitely are not in the petroleum
and tobacco industries.

24



'

where / is actual investment in
year t\ 7 is the smoothed invest­
ment series discussed above; A is a
measure of the state of the aggre­
gate economy; and e is the error
term. The measure of aggregate
economic activity is lagged by one
period because the peaks and
troughs of the aggregate invest­
ment cycle typically lag slightly
the peaks and troughs of aggregate
GNP.1
2
We considered three alterna­
tive measures of A. One measure
was the ratio of actual to potential
GNP as measured by the Federal
Reserve Board.1 A second meas­
3
ure was the ratio of current capac­
ity utilization in manufacturing to
average capacity utilization. The
final measure was the ratio of the
actual rate of unemployment to the
natural rate of unemployment. All
three measures have potential
shortcomings. Fortunately, the
results were qualitatively the same
for all three measures. Therefore
we report results for only the first
measure and briefly summarize the
results for the other two measures;
that is, for each industry, we report results for
the following regression:
GNP ,
/
_ _ _ _ _1 - 1
2A) j = a+b
POTGNPi-i C
'
Table 3 shows our findings for the manu­
facturing sector and its component two-digit
industries for the regression given in Equation
(2A). To economize on space, we do not re­
port the intercept terms, which were statisti­
cally insignificant in all but one regression.
For each industry, we report three statistics:

ECONOMIC PERSPECTIVES

the slope coefficient for the state of
FIGURE 4
the economy variable, the standard
Indexed real investment
error of the variable, and the
(SIC 35: Industrial machinery and equipment)
adjusted / -square of the regression.
index, 1958=100
We start with the obvious. For
the manufacturing sector as a
whole, the estimated coefficient is
positive and significant at a very
high confidence level. In other
words, investment in manufacturing
is procyclical. This is not a very
surprising result; we would be hard
pressed to explain a different find­
ing. What is more interesting is
that our regression results indicate
that investment in manufacturing is
more cyclical than aggregate GNP;
our estimated coefficient of 2.23
implies that investment is approxi­
mately 2 percent above trend fol­
lowing a period when GNP is 1 per­
cent above potential GNP. In addi­
tion, it is interesting to note that our
single regressor is explaining a con­
siderable fraction (40 percent) of
the variation of actual investment
around trend investment.
We turn now to the two-digit
industry results. A cursory look at
the results indicates a considerable
range of point estimates across the
20 industries. The smallest coeffi­
cient, -1.36, is for SIC 21 (tobacco
products), while the second small­
est is for SIC 20 (food products).
At the other end of the scale, SIC
37 (transportation) has an estimated
coefficient of 3.79, while the next
largest coefficient is for SIC 33
(primary metals). For all but SIC
21 (tobacco) the point estimate for the slope
coefficient is positive. Of these nineteen in­
dustries, all but three (SIC 20, SIC 29, and SIC
slope coefficients greater than the manufactur­
39) have estimated slope coefficients of
ing average; that is, they exhibit more procy­
greater than one.
clical investment than average.
We believe the most interesting finding of
The first group, SIC 20 through SIC 31,
our research is the clean separation into two
can be characterized approximately as the
groups, with respect to cyclical investment be­
nondurable-goods sector of manufacturing.
havior, of the 20 two-digit industries. The
With one exception, every one of these indus­
group consisting of SIC 20 through SIC 31 as
tries has an estimated slope coefficient of less
well as SIC 39 (miscellaneous manufacturing)
than the all-manufacturing coefficient of 2.23.
exhibits slope coefficients of less than the
For seven of these industries, the estimated
overall manufacturing average of 2.23. The
standard error is large enough that one cannot
other group, SIC 32 through SIC 38, exhibits

FEDERAL RESERVE



BANK OF CHICAGO

25

TABLE 3

Regression results: Investment ratio versus

G N P

ratio

Slope coefficient

Standard error

2.227

0.502

0.609

0.296

0.104

-1.361

1.450

-0.004

SIC 22 - Textile m ill products

1.530

0.889

0.066

SIC 23 - A p p arel and related products

1.825

0.687

0.178

Total Manufacturing
SIC 20 - Food and kindred products
SIC 21 - Tobacco products

R

Square (adjusted)
0.400

SIC 24 - Lum ber and w ood products

1.928

1.138

0.063

SIC 25 - Furniture and fixtures

1.296

1.014

0.022

SIC 26 - Paper and allied products

2.129

0.786

0.185

SIC 27 - Printing and publishing

1.710

0.683

0.158

SIC 28 - Ch em icals and allied products

1.903

0.769

0.155

SIC 29 - Petroleum and coal products

0.976

1.478

-0.021

SIC 30 - R ubber and plastic products

2.320

1.105

0.108

SIC 31 - Leather and leather products

1.228

1.448

-0.010

SIC 32 - Stone, clay and glass products

2.299

0.880

0.172

SIC 33 - Prim ary metal industries

3.368

1.008

0.266

SIC 34 - Fabricated metal products

2.389

0.635

0.320

SIC 35 - M achinery, except electrical

3.022

0.686

0.396

SIC 36 - Electrical m achinery

2.248

0.691

0.255

SIC 37 - Transportation equipm ent

3.789

1.360

0.195

SIC 38 - Instrum ents and related products

2.528

0.959

0.175

SIC 39 - M iscellan e ou s m anufacturing

0.760

0.813

-0.005

reject the hypothesis at a 5 percent confidence
level that investment is acyclical. For SIC 23,
26, 27, 28, and 30, the estimated coefficients
are large enough to reject the hypothesis of
acyclical investment behavior. However, one
cannot conclude that their investment is more
cyclical than GNP. Finally, it is interesting to
note that while the previous section indicated
that the petroleum (SIC 29) and tobacco (SIC
21) industries have very volatile investment
series, they do not exhibit procyclical invest­
ment behavior.
The other group, SIC 32 through SIC 38,
consists of all durable-goods industries. All of
these industries have slope coefficients greater
than the manufacturing average, most noticea­
bly for transportation (SIC 37), primary metals
(SIC 33), and nonelectrical machinery (SIC
35). These three industries, along with fabri­
cated metal products (SIC 34), have large
enough coefficients relative to their standard
errors such that one can reject the hypothesis
that their slope coefficient is less than one.
The transportation industry is particularly
noteworthy, given the volatility of its invest­
ment series combined with its very high slope
coefficient.

26



The durable-goods sector has long been
known to have more cyclical output than the
nondurable-goods sector. It also appears to be
the case that investment across virtually all of
the durable-goods two-digit industries is more
cyclical than investment in the nondurablegoods industries. This pattern of results was
confirmed for all measures of aggregate eco­
nomic activity that were used as regressors in
Equation 2, including capacity utilization and
unemployment.
C onclusion

Studies of investment typically use either
aggregate investment numbers or firm level
data. We believe, however, that useful knowl­
edge can be obtained by examining the invest­
ment behavior at the industry level. Using a
panel database of 270 four-digit industries
over the period 1958-1986, we have examined
the volatility and cyclicality of investment for
all 20 of the two-digit Census of Manufactures
industries.
We find that there is a great deal of
heterogeneity across these industries. Some
industries, such as transportation, petroleum,
and tobacco, exhibit considerable investment

ECONOMIC PERSPECTIVES

volatility. We show, however, that industries
which have the most volatile investment series
do not necessarily exhibit the most cyclical
investment series.
The major question that our article sought
to answer is: Are there important differences
in the cyclicality of investment across manu­
facturing industries? Our findings indicate
that there are. With one exception, industries
in SIC 20 through SIC 31 have estimated
measures of cyclicality that are less than the
manufacturing average for our sample. The
remaining group of industries, SIC 32 through
SIC 38, which consists of durable-goods
manufacturers, appears to be more cyclical
than the manufacturing average. The transpor­
tation industry leads the way followed by the
primary metals and nonelectrical machinery.

While it has long been known that the
durable-goods sector has larger cyclical swings
in output and profits than the nondurablegoods sector, it also appears that the durablegoods sector has larger cyclical swings in the
accumulation of capital. Thus, our results
shed some doubt on the view that our econ­
omy’s large swings in aggregate investment
are primarily caused by firms’ efforts to read­
just their capital stocks in response to changes
in real rates of interest. Models of investment
that focus only on the cost of capital appear to
be missing some important determinants of
investment behavior. Given the well docu­
mented swings in output and profits in the
durable-goods sector, the likely missing deter­
minants are accelerator effects and internal
finance considerations.

FOO TNOTES
'These values are taken from Barro (1987, p. 226), which
contains a more detailed discussion of the facts concerning
the cyclicality o f aggregate investment.

the current year and the data for the next four years. Of
course, for the years near our endpoints, fewer years of data
were available for computing this average. See Pindyke
and Rubinfeld (1981) for details.

2See Barro (1987, p. 229).
T or a more detailed discussion of these models of invest­
ment, see Gordon (1984) or Kopcke (1985).
4See for example Barro (1987, p. 247).
5Recent papers which present evidence supporting the view
that fluctuations in cash flow are an important source of
fluctuation in investment include Fazzari, Hubbard, and Pe­
tersen (1988), HOshi, Kashap, and Scharfstein (1989), and
Kopcke (1985).

9We experimented with different n values for Equation 1
and found that the results reported in the article are robust
to a wide range of different values for n.
1 Charts for the remaining two-digit industries are available
0
from the authors upon request.
"The coefficient of variation is the ratio of the standard
deviation to its mean. The standard deviation is an absolute
measure of dispersion measured in units of the original
data. By contrast, the coefficient of variation is dimension­
less and measures relative dispersion.

‘It is well known that the Census periodically changes the
definitions o f some industries, often by merging portions of
one industry with pieces of another. This provides the
biggest challenge to utilizing the Census of Manufactures.
Since we did not want our findings to be biased by changes
in reported investment arising from industry reclassifica­
tion, we thought it necessary to exclude all industries that
underwent a significant reclassification. More details on
the construction o f the panel can be found in Domowitz,
Hubbard, and Petersen (1986).

1
2We also considered contemporaneous A as well as A
lagged by two years. The regression results for total manu­
facturing, based on a considerably higher adjusted /-square,
prefers A lagged by one period over contemporaneous A.
At the two-digit industry level the results of contemporane­
ous versus one-year lag were roughly the same. However,
for A with a two-year lag, there is no statistically significant
relationship between investment and the two-year lagged
state of the economy.

7The current dollar investment by two-digit SIC code
industries were adjusted for inflation by dividing each of
the series by the producer price index for capital goods.

"Potential GNP is from estimates made by staff members
o f the Board of Governors. For the methodology underly­
ing these estimates see Clark (1982).

8The centered moving average approach that we utilized
averages the data for the previous four years, the data for

FEDERAL RESERVE



BANK OF CHICAGO

27

REFERENCES

Barro, Robert J., Macroeconomics, New
York: John Wiley & Sons, 1987.
Clark, Peter K., “Okun’s Law and Potential
GNP,” Board of Governors of the Federal
Reserve System, October 1982.
Domowitz, Ian, R. Glenn Hubbard, and
Bruce C. Petersen, “Business Cycles and the
Relationship Between Concentration and
Price-Cost Margins,” Rand Journal of Eco­
nomics, Vol. 17, No. 1, Spring 1986, pp. 1-17.
Fazzari, Steven M., R. Glenn Hubbard, and
Bruce C. Petersen, “Financing Constraints
and Corporate Investment,” Brookings Papers
on Economic Activity, Vol. 1, 1988, pp. 141195.
Gordon, Robert J., Macroeconomics, Boston:
Little, Brown and Company, 1984.
Hoshi, Takeo, Anil Kashap, and David
Scharfstein, “Corporate Structure, Liquidity,
and Investment: Evidence from Japanese Panel
Data,” Federal Reserve Board Working Paper,
June 1988.
Kopcke, Richard W., “The Determinants of
Investment Spending,” Federal Reserve Bank
of Boston, New England Economic Review,
July/August 1985, pp. 19-35.

Kuh, Edwin, Capital Stock Growth: A MicroEconometric Approach, London: North-Holland Publishing Company, 1971.
Meyer, John R., and Robert R. Glauber,
Investment Decisions, Economic Forecasting,
and Public Policy, Boston: Division of Re­
search, Graduate School of Business Admini­
stration, Harvard University, 1964.
Meyer, John R., and Edwin Kuh, The Invest­
ment Decision: An Empirical Study, Boston:
Harvard University Press, 1957.
Modigliani, Franco, and Merton H. Miller,
“The Cost of Capital, Corporation Finance and
the Theory of Investment,” American Eco­
nomic Review, Vol 48 June 1958, pp. 261 297.
Pindyke, Robert S., and Daniel L.
Rubinfeld, Econometric Models and Eco­
nomic Forecasts, New York: McGraw-Hill
Book Company, 1981.
U.S. Department of Commerce, Census of
Manufactures, selected issues.
___________________________ , Annual
Survey of Manufactures, selected issues.

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