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Ft
E
July/August 1994
Vol. 76, No. 4
II
Exp lan ation s for the In creased R iskiness of
Banks in the 19 8 0 s
Trade Betw een the United States
and Eastern Europe
The New Stru ctu re o f the Housing
Fin an ce System
The Inflation Tax and the M arginal W elfare
Cost in a W orld o f C urren cy and Deposits
THE
FEDERAL
A RESERVE
BANK of
ST. LOUIS
R E V I E W
President
T h o m a s C. M e lz e r
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1
Federal Reserve Bank of St. Louis
Review
July/August 1994
In This Issue...
Explanations for the Increased Riskiness of Banks in the 1980s
Sangkyun Park
In the 1980s, the number of bank failures increased sharply, and banks
in general experienced increasing problem loans and dwindling capital.
The main explanations for the deterioration of bank asset quality include
increased incentives for risk-taking by bank stockholders, desperate risktaking by bank managers to increase profits, and unexpected economic
shocks. Sangkyun Park reviews the logic of the three explanations and
examines their empirical significance. He finds that deliberate risk-taking
by both stockholders and managers was consistent with the behavior of a
sizable proportion, though not the majority, of banks. He also concludes
that economic shocks were significant, but do not negate the effects of
deliberate risk-taking.
25
Trade Between the United States and Eastern Europe
Patricia S. Pollard
Most of the trade between the United States and Eastern Europe since
the end of World War II has been very small. W hile the United States
has maintained high tariffs on imports from most Eastern European
countries— and restricted its own exports to them as well, particularly
high technology—Eastern Europe has maintained trade restrictions on
imports from the United States. W ith the collapse of the Soviet system,
however, Eastern Europe has begun to re-direct trade to the West as it
initiates both political and economic reforms.
Patricia S. Pollard describes the recent changes in trade flows between the
United States and the three Eastern European countries that have made
the greatest progress in adopting market reforms: the Czech and Slovak
Federal Republic (CSFR), Hungary and Poland. She concludes that
increased trade between the East and the West benefits not only the
United States’ economy, but is also directly linked to Eastern Europe’s
efforts to establish and maintain political stability.
47
The New Structure of the Housing Finance System
John C. W eicher
The Financial Institutions Reform, Recovery and Enforcement Act of 1989
(FIRREA) marked both the culmination of a 20-year period of changes in
the U.S. housing finance system and the beginning of a period of legislative
reforms intended to forestall any recurrence of the savings-and-loan
industry debacle that forced the enactment of FIRREA.
JULY/AUGUST 1994
2
John C. Weicher describes the process of change in the housing finance
system and its implications for the ability of the system to fulfill the pur
poses for which it was established. The new system is dominated by two
large national institutions, chartered by the federal government and serving
the secondary mortgage market, instead of thousands of small, local lenders
who both make mortgage loans and hold them in portfolios. Legislation of
the last five years has imposed higher capital requirements on nearly every
institution involved with housing finance and changed the regulatory
structure for every private institution in the system. In addition, these
changes have created potential conflicts with the stated public objectives
of the system: access to home mortgage funds for areas and groups that
are “underserved” and support for the mortgage market during
economic downturns.
67
The Inflation Tax and the Marginal Welfare Cost in a World of
Currency and Deposits
Alvin L. Marty
Since inflation is the rate at which the purchasing power of money declines,
it is a tax on real money balances. Alvin L. Marty provides an analysis that
determines the optimal rate of inflation as an efficient tax rate. He explains
the government’s revenue and the total cost associated with inflation and
how each is affected by the level of the inflation rate. An efficient tax system
minimizes the total cost of collecting a given tax revenue. For inflation to
be chosen as a component of an efficient tax system, however, the inflation
rate must be set so that the marginal cost per dollar of government revenue
from inflation is equal to the marginal cost per dollar of other sources of
revenue. Marty shows how the analysis of such an optimal rate of inflation
is altered when there are two components of money—currency and
deposits— one produced directly by the government, or its central
bank, and the other provided by a competitive banking system.
FEDERAL RESERVE BANK OF ST. LOUIS
3
Sangkyun Park
Sangkyun Park is a senior economist at the Federal Reserve
Bank of St. Louis. Jonathan Ahlbrecht provided research
assistance.
Explanations fo r the Increased
Riskiness of Banks in the 1980s
X N T E R E S T IN BANKING MATTERS surged
in the 1980s, when the U.S. banking system
experienced considerable difficulties after several
decades of stability. During the decade, the
number of bank failures increased sharply, and
banks in general experienced increasing problem
loans and dwindling capital. Most banks recov
ered their financial strength in the early 1990s
thanks to improved economic conditions and
low short-term interest rates that increased
interest margins. With the recovery of the banking
sector, public interest in bank failures is fading,
but many questions remain unanswered. To
effectively prevent repetition of the banking
turmoil, it is important to study the fundamental
causes of the sudden deterioration of the financial
health of the banking system in the 1980s.
Without recognizing the causes, future banking
policies intended to improve the safety and
soundness of the banking sector might produce
more unintended effects than intended ones.
Numerous studies have proposed explanations
for the deterioration of bank asset quality, but
empirical evidence is sketchy. This study explores
theoretical explanations for the financial problems
of commercial banks in the 1980s and examines
their empirical consistency. I focus on commer
cial banks because many previous studies have
examined the financial problems of savings and
loan associations (S&Ls). Three theoretical
possibilities for the increased riskiness of banks
in the 1980s are considered: (1) increased incen
tives for risk-taking by bank stockholders; (2)
desperate attempts of bank managers to increase
profits by assuming additional risk; and (3)
unexpected economic shocks.
To evaluate the empirical significance of the
three hypotheses, the empirical section examines
the effects of capital adequacy and earnings on
the risk-taking behavior of banks and also looks
at the relationship between regional economic
conditions and bank performance. Capital ratios
and earnings may be related to the risk-taking
incentives of stockholders and managers, respec
tively. Regional economic conditions should
largely explain bank performance if unexpected
economic shocks are the main reason for the
deterioration of bank asset quality. For selected
years of the 1980s, I divide banks into several
groups based on year-end capital ratios and
earnings on assets. I then compare year-to-year
changes in various risk measures across groups.
Although deliberate risk-taking by stockholders
and managers does not appear to apply to the
majority of banks, it is found to be consistent
with the behavior of a sizable proportion of
banks. This result holds even after controlling
for the effects of local economic conditions.
The next section describes the economic and
institutional developments that are related to
JULY/AUGUST 1994
4
the financial troubles in banking during the 1980s.
The following section explores theoretical expla
nations for increased risk-taking and existing
empirical evidence. Empirical results of this
study follow. Lastly, the article’s findings
are summarized.
DEVELOPM ENTS IN BANKING
The United States enjoyed stable banking during
the four decades following the establishment of
the Federal Deposit Insurance Corporation (FDIC)
in 1934. The relatively high number of bank
failures between 1934 and 1942, about 44 per year,
may be regarded as an aftermath of the financial
crisis of 1933 and the following years of depressed
economic activity.1 Between 1943 and 1974, only
121 banks failed. Bank failures began increasing
in the second half of the 1970s and became notable
in the second half of the 1980s. Between 1985
and 1990, the number of bank failures averaged
169 per year. To understand the dramatic
increase in bank failures, we need to look at
the economic and institutional developments
that are relevant to the banking business.
Econom ic Developments
The banking industry encountered numerous
unfavorable shocks in the 1970s and 1980s. These
included sudden increases in interest rates, the
collapse of many real estate investment trusts
(REITs), the Latin American debt crises and sharp
declines in real estate values. High inflation in
the 1970s and the early 1980s raised interest rates.
Unexpected increases in interest rates usually
lower bank interest margins because the average
maturity of bank liabilities is generally shorter
than that of their assets. The mismatch of matu
rities means that lending rates adjust more slowly
than funding rates. Increases in interest rates,
hence, tend to lower bank profits.
REITs, which channel investors’ money into
the real estate, mortgage and construction markets,
grew rapidly in the early 1970s. Banks were the
major supplier of funds during the rapid expan
sion and often served as REIT advisors, whose
functions included proposing investment projects
and overseeing daily operations.2 A slump in
the construction and real estate industries in the
1 The bank failure numbers do not include uninsured banks.
See FDIC (1991).
2 See Sinkey (1979) for a detailed discussion of REITs.
3 See Cline (1984) for a detailed discussion of sovereign debt
crises.
FEDERAL RESERVE BANK OF ST. LOUIS
m id-1970s decreased the asset value of many
REITs and the banks that extended credit to them.
After the oil shock of 1974, oil-exporting coun
tries enjoyed large trade surpluses. U.S. banks
took an active role in channeling the surpluses
to developing countries. As a result, loans by
U.S. banks to developing nations increased
rapidly during the 1970s to exceed $100 billion
in the early 1980s, when sovereign debt problems
emerged.3 Large developing-country debtors,
including Brazil, Mexico and Argentina, failed
to meet their debt obligations as they were strained
by worldwide recession, high interest rates and
the second oil shock in 1979. Their debt-servicing
difficulties lowered the value of the loans and,
hence, the value of lending banks’ capital.
A real estate boom in the 1980s resulted in
sharp increases in property prices and over
building of commercial properties in many
parts of the United States. Banks financed
the boom by expanding loans rapidly. Toward
the end of the decade, the value of commercial
properties plunged as vacancy rates surged.
The price of residential properties also dropped
in some regions, the Northeast and California in
particular, where income growth substantially
lagged behind increases in housing prices.
Declining real estate prices placed many banks
in financial trouble by increasing delinquency
rates and lowering collateral values.
Institutional Developments
The Banking Act of 1933 transformed a rela
tively competitive banking system into a highly
protected one. Before its enactment, the main
barrier to competition was the prohibition of
interstate branching. The Banking Act of 1933,
however, insulated the banking business by pre
venting banks from engaging in other businesses,
including the securities business, and vice versa.
It also prohibited payment of interest on demand
deposits and authorized the Federal Reserve
Board to limit interest rates on time and savings
deposits at member banks. Most notably, the
act created the FDIC.
The above measures relieved banks from com
petitive pressure. The continued prohibition of
interstate branching preserved some geographic
5
monopoly power. The separation of banking
from other industries bolstered monopoly power
by deterring other businesses from making inroads
into banking. With interest rate ceilings, banks
were unable to bid up interest rates to attract
deposits. Government-backed deposit insurance
made it unnecessary for banks to prove their
soundness to depositors. Protected from compe
tition, banks enjoyed relatively stable market
shares and profits.
Legislative and institutional developments
in the 1970s and 1980s relaxed regulation and
permitted greater competition. Many states
relaxed their restrictions on bank ownership by
out-of-state holding companies. This develop
ment lowered geographic entry barriers, despite
the prohibition of interstate branching.4
The Depository Institutions Deregulation and
Monetary Control Act of 1980 (DIDMCA), which
phased out interest ceilings and permitted all
depository institutions to offer NOW accounts,
allowed greater competition for deposits among
banks. This act, in combination with the GarnSt. Germain Depository Institutions Act of 1982,
also increased competition between banks and
S&Ls by expanding the realm of the S&L business.
Institutional developments also added compet
itive pressure on banks. The 1980s witnessed
rapid growth of financial products that could
substitute for banking products.5 For example,
many large corporations with established credit
records found it attractive to borrow directly by
issuing commercial paper. Money market mutual
funds began offering convenient features of bank
deposits such as checking privileges, and purchases
and redemptions without fees. The emergence of
competing products offered by nonbank institu
tions eroded the profitability of banks.
In sum, the banking industry experienced
unfavorable economic shocks and increased
competition in the 1970s and 1980s. Slumps
in real estate markets and sovereign debt crises
impaired the financial health of many banks.
Legislative changes lowered geographic entry
barriers and restored the mechanism of price
competition in the banking sector. In addition,
increasing sophistication of financial markets
enabled nonbank institutions to circumvent
industry barriers.
TH EO RETICAL EXPLANATIONS AND
EXISTIN G EVIDENCE
Numerous studies have proposed explanations
for the deterioration of bank asset quality during
the 1980s, which can be broadly classified into
three groups. First, “moral hazard” explanations
argue that the changed economic and institutional
environment in the 1980s increased the incen
tives of bank stockholders to take risk. A second
explanation is increased risk-taking incentives
of managers, rather than stockholders. A third
possibility is that the quality of bank assets
deteriorated mainly because of unexpected
external events rather than deliberate risk-taking.
The three explanations are generally consis
tent with developments in the banking sector.
Convincing conclusions require detailed empirical
examination. Unfortunately, the difficulty of
obtaining adequate risk measures has discouraged
empirical examination. Furthermore, it is difficult
to determine causality because the hypotheses
are interrelated with one another. For example,
a negative economic event that decreases bank
capital may increase the incentive to take risk,
and risk-taking may make banks more vulnerable
to economic shocks.
Moral Hazard
Stockholders im plicitly hold a put option,
the right to sell their stocks at a prespecified
price. With limited liability, stockholders of a
corporation can walk away without incurring
further losses when the net worth of the corpora
tion falls below zero. Escaping from a firm with
a negative net worth is eco n o m ica lly equivalent
to selling the firm for the price of zero. Stock
holders can thus increase their expected wealth
at the expense of debtholders by increasing the
variance of the return from assets, that is, by taking
more risk. With a larger variance, it is more
likely that the return from assets will turn out to
be very high. A larger variance also increases
the possibility of an extremely low return and,
hence, a substantially negative net worth.
Limited liability, however, protects stockholders
4 According to unpublished data compiled by the Board of
Governors, bank assets held by out-of-state bank holding
companies totaled about $470 billion as of June 30,1990,
which accounted for about 16 percent of total bank assets.
5 Wheelock (1993) discusses the increasing competition faced
by banks both in lending and funding markets.
JULY/AUGUST 1994
6
from incurring additional losses once net worth
has fallen to zero. In other words, while improved
upward potential of asset portfolios clearly ben
efits stockholders, downside risk mainly harms
debtholders. Thus, limited liability gives stock
holders an incentive to take higher risk than
they otherwise would.
In general, market forces prevent stockholders
from taking advantage of the put option value.
Debtholders demand interest rates high enough
to compensate for higher default risk when a
corporation holds a risky portfolio. In addition,
bond covenants and needs to refinance short-term
debt restrict the portfolio selection of corporations.
Thus, it is difficult for stockholders to exploit
debtholders because the cost of debt increases
with the riskiness of a corporation. The effec
tiveness of this market mechanism is limited in
the banking sector, however, because of government-backed deposit insurance. In the 1980s,
most deposits were insured either explicitly or
im plicitly.6 Thus, most depositors, who were
the major debtholders of banks, were indifferent
about the riskiness of individual banks and,
hence, did not demand higher interest rates to
riskier banks. Furthermore, the FDIC charged a
fixed-rate insurance premium until the end of
1992. Therefore, banks enjoyed risk-insensitive
funding costs and had greater incentives to take
risk than they would have if deposits were not
insured.7 Because of the risk-taking incentives
created by deposit insurance, banking authorities
need to lim it the portfolio selection of banks.8
In other words, government action must substi
tute for market forces to prevent banks from
taking excessive risk.
Proponents of the moral hazard view argue that
banks had increased incentives to take risk in the
1980s for two main reasons: losses that impaired
capital and reduced charter values due to greater
competition.9 Poorly capitalized banks have a
greater incentive to take risk. With smaller capital,
6 Studies on market discipline find that the presence of large
deposits exceeding the FDIC insurance limit of $100,000
was not an effective source of discipline on banks. Gilbert
(1990), who surveys the market discipline literature, points
out that uninsured depositors and holders of subordinated
debt rarely absorbed losses of failed banks. In most cases,
failed banks were merged with other banks, and the acquir
ers assumed all liabilities of the failed banks.
7 Merton (1977) makes theoretical arguments based on the
option-pricing model.
8 Calomiris (1989) compares deposit insurance systems in
U.S. history and concludes that a necessary condition for
the success of deposit insurance systems is effective
enforcements of regulations.
Digitized for FEDERAL
FRASER RESERVE BANK OF ST. LOUIS
it is more likely that losses will be born ultimately
by debtholders. Stockholders have less exposure
to losses when capital is low and, hence, are less
concerned about probable losses resulting from
risk-taking.
In addition to tangible capital, firms have charter
values, which may be defined as the economic
value deriving from the opportunity to do business
in the future. If a firm fails, it loses its charter
value. Thus, firms with large charter values may
refrain from taking risk and inject more tangible
capital to avoid failure. Effective restrictions on
competition raise charter values. When there is
less competition, the opportunity to do business
in the future is more valuable because firms can
expect larger profits. Increased competition in
the banking sector in the 1980s reduced the
charter value of banks and, hence, increased
their incentives to take risk.10
Empirical tests of the moral hazard hypothesis
present mixed results. Gunther and Robinson
(1990) examine the behavior of insured commer
cial banks in the Dallas and Houston metropolitan
areas between 1983 and 1984 and find a negative
relationship between capital growth and changes
in loan-to-asset ratios. They interpret this result
as a negative relationship between capital adequacy
and risk-taking. Other studies examine S&L data.11
Barth and others (1986) find that delay in closing
insolvent S&Ls increased the resolution costs to
the Federal Savings and Loan Insurance Corpora
tion between 1981 and 1985. They suggest that
desperate risk-taking by insolvent institutions
was largely responsible for the increased costs.
McKenzie and others (1992) compare returns of
thrifts in 1987 and 1988 on traditional and nontraditional assets allowed by the DIDMCA and
the Garn-St. Germain Act. They find that returns
were generally lower on nontraditional assets,
particularly on those held by capital-deficient
institutions, than on traditional assets. They
conclude that low-capital thrifts undertook
9 See Marcus (1984) and Keeley (1990). Relaxed portfolio
restrictions are frequently cited as a main cause of the
increased risk-taking by S&Ls. The increased risk-taking
opportunities are relevant but not equally important to banks.
The DIDMCA of 1980 and the Garn-St. Germain Act of 1982
substantially relaxed restrictions on S&L assets but did not
notably loosen constraints on bank assets.
10 Keeley (1990) finds a relationship between risk-taking by
banks and declining charter values during the 1980s.
11 The risk-taking behavior of S&Ls may be similar to that of
banks in many respects. Both banks and S&Ls benefited
from deposit insurance and underwent economic shocks
and regulatory reform in the 1970s and 1980s.
7
projects with low net present values to increase
the variance of the return and, hence, took more
active advantage of risk-taking opportunities
opened by legislative changes.
While the studies discussed above support
moral hazard theories, some others fail to find
evidence of moral hazard. According to Benston
and Carhill (1992), investment in nontraditional
assets was a major cause of thrift failures that
occurred between 1985 and 1991, but that
investment was undertaken primarily by initially
solvent thrifts. Thus, the shortage of capital was
a result, rather than a cause, of increased risk.
Gilbert (1991), who studies the behavior of under
capitalized banks between 1985 and 1989, shows
that banks reduced their assets substantially while
undercapitalized. This finding does not support
a negative relationship between the capital ratio
and risk-taking. In addition, recent studies on
the credit crunch find a positive relationship
between the capital ratio and loan growth in
the early 1990s.’2
Incentives o f M anagers
Moral hazard theories assume that managers
maximize stockholder wealth. Some recent
studies, however, suggest that the incentives
of managers may differ from those of outside
shareholders.13 Managers of failed banks may
have difficulty finding comparable positions.
Thus, bank failure reduces expected future
earnings of the bank’s managers. In this regard,
bank managers are similar to stockholders with
a large charter value who tend to refrain from
taking risk. Furthermore, managers, whose com
pensation packages are predetermined in many
cases, may not benefit as much from risk-taking
as stockholders.14 In addition, it is difficult for
stockholders to monitor managers due to the
12 For example, Johnson (1991), Bernanke and Lown (1991)
and Peek and Rosengren (1992). Since tightened capital
requirements implemented in the early 1990s can partly
explain the contraction by capital-deficient banks, the credit
crunch does not necessarily contradict moral hazard.
Nevertheless, their findings are still suggestive of the magni
tude of moral hazard problems.
problem of analyzing the quality of existing
assets and investment opportunities. Many
studies recognize that stockholders are not as
well-informed as managers about the earnings
prospects of firms.15 These arguments suggest
that managers may not act in the best interest
of stockholders.
In general, managers may prefer not to take
as much risk as stockholders want because they
face a larger cost and a smaller benefit from addi
tional risk.16 Many managers, however, may
adopt extremely risky strategies under certain
conditions, namely, when a large proportion
of managers are incompetent and profits are
declining.17 The banking sector appears to
have satisfied these conditions in the 1980s.
Incompetent managers, who cannot effectively
control costs and make wise investment choices,
may need to pursue more risky strategies to keep
their jobs longer. Stockholders want managers
to be competent and loyal to them. When stock
holders are not accurately informed about the
future earnings prospects of their banks, they
may rely on some easily identifiable measures
to judge the quality of management. Earnings
records may reflect the quality of a bank’s man
agement. If a bank takes high risk as demanded
by stockholders, it will occasionally suffer low
earnings resulting from unlucky outcomes.
Managers are not to blame in that case. Stock
holders may fire managers, however, if earnings
turn out to be consistently lower than the industry
average. Of course, consistently below-average
earnings may be a result of bad management.
Since incompetent managers cannot do as well
as competent ones on average, a conservative
strategy by incompetent managers w ill consis
tently result in below-average earnings. One way
they can occasionally have above-average earnings
not seem to apply to the banking industry of the 1980s,
when banks suffered low profits.
17 Gorton and Rosen (1992) present a game-theoretic model
showing that banks on average pursue risky strategies in
these conditions.
13 See Saunders and others (1990), Allen and Cebenoyan
(1991) and Gorton and Rosen (1992).
14 Houston and James (1993) fail to find any evidence that the
structure of management compensation in banking serves to
reward managers for exploiting risk-taking opportunities.
16 See Myers and Majluf (1984), Miller and Rock (1985) and
MacKie-Mason (1990).
16 Jensen (1986) argues that managers with large free cash
flow may expand their firms beyond the optimal size to
increase their power and perquisites. This argument does
JULY/AUGUST 1994
8
is to take on high-variance projects. Occasional
high earnings can confuse stockholders, making
judgements about the quality of management
difficult. Thus, taking risk may be a rational
strategy for incompetent managers. Intuitively
speaking, one has to take chances and hope for
good luck if he or she cannot rely on ability.
In a tightly regulated industry, incompetent
managers may be able to survive without taking
excessive risk because stockholders do not
observe much difference between competent
and incompetent managers.18 Even incompetent
ones can generate decent profits when there is
little competition. Moreover, it is difficult for
competent managers to excel if competition is
limited by regulation. Considering that the
banking business was tightly regulated until the
early 1980s, the proportion of incompetent man
agers may have been higher in the banking sector
than other industries. Deregulation increased
competition, and the banking industry experi
enced declining market shares and profitability
in the 1980s. When tight cost control and hard
search for profit opportunities are called for,
disparities between competent and incompetent
managers become clear because managerial ability
plays a significant role. The banking develop
ments in the 1980s may have induced some
incompetent bank managers to take excessive
risks in a desperate attempt to preserve their jobs.
Thus, it is possible that a change in managers’
incentives may have been largely responsible
for the increased riskiness of banks.
Evidence of risk-taking driven by the incentives
of incompetent managers is indirect and limited.
Gorton and Rosen (1992) show that “entrenched”
mangers made more risky loans between 1984
and 1990 and interpret the result as evidence
that excessive risk-taking was driven largely by
managers’ incentives.19 Allen and Cebenoyan
(1991) find that the most powerful managers
actively acquired other banks between 1980 and
1987 and that those acquisitions were not valueenhancing.20 Although the focus of their study
is not risk-taking by banks, this result is consistent
with that of Gorton and Rosen.
18 Flood (1993) also argues that incompetent managers can
survive indefinitely in a protected industry.
19 By their definition, entrenched managers are the mangers
with enough shares to be protected from outside shareholders’
pressure but not enough shares to have the same objective
as that of outside shareholders.
20 The power of managers increases with managerial stake
and decreases with concentration of outsiders’ shareholdings.
Digitized forFEDERAL
FRASER RESERVE BANK OF ST. LOUIS
U nexpected Shocks
Given that banks experienced many external
events that impaired their financial structure in
the 1970s and 1980s, deliberate risk-taking is not
required to explain the increased riskiness of
banks. Banks may not have realized that certain
categories of loans were particularly risky until
many borrowers became unable to repay. Con
sidering that geographic and portfolio restrictions
limit the ability of banks to diversify, the financial
strength of banks may greatly depend on the
quality of major-category loans.
Before the establishment of the FDIC, banking
distress was often triggered by the collapse of a
major industry or a stock market crash. In the
19th century, it was not unusual for banks to
finance the expansion of a booming sector such
as cotton or railroads, only to experience finan
cial difficulties when that sector went bust.21 In
those cases, deterioration in the asset quality of
banks could hardly be attributed to increased
risk-taking incentives resulting from institutional
changes because the banking sector was governed
largely by market forces at that time. Thus, it
is possible that realization of highly unlikely
outcomes or judgement errors were largely
responsible for the financial problems of banks
in the 1980s. Banks became extremely unlucky,
or they unknowingly, rather than deliberately,
increased the variance and lowered the expected
value of their asset portfolios because of inability
to assess the soundness of investment opportu
nities. For example, banks might have expected
that the real estate boom of the 1980s would
continue for a long time and were surprised
by the bust.
McKenzie and others (1992) and Emmons
(1993) find that the condition of local economies
significantly contributed to the earnings and
failures of financial institutions. These results
imply that external shocks had significant
effects on the performance of banks, but does
not disprove the role of deliberate risk-taking.
Risk-taking generally makes banks more vulner
able to external shocks.
21 Park (1993) examines the economic environment that led to
banking panics.
9
EM PIRICAL STUDY
To test the relevance of each hypothesis for
explaining bank risk in the 1980s, we need to
empirically examine the implications of each
hypothesis using a consistent sample and com
parable methodology. The application of rigorous
econometric techniques to the risk-taking behavior
of banks involves many problems, such as deter
mining appropriate measures of risk and specifying
a reasonable functional form. To avoid these
difficulties, this study divides banks into several
groups based on year-end capital ratios and
earnings on assets for selected years, and com
pares changes in various risk measures such
as loan growth, the proportions of risky loans
and funding strategies during the following
year across groups. By looking at the behavior
of banks in following years, we can better deter
mine causality. It is difficult to infer causality
from contemporaneous relationships because
risk measures interact with capital ratios and
earnings. For example, a low capital ratio can
be either a cause or a result of increased risk.
Aggressive risk-taking by poorly capitalized
banks may be interpreted as evidence of moral
hazard; stockholders more actively took advan
tage of deposit insurance when they did not
have much of their own wealth to lose. The
association of low earnings with more risk-taking
can be an indication of desperate profit-seeking
by incompetent managers. Incompetent managers,
who are more likely to have low earnings, may
have adopted risky strategies to obscure their
incompetence with occasional high earnings.
The hypothesis of unexpected economic shocks
may be supported by insignificance of capital
adequacy and earnings along with significance
of the condition of local economies in explaining
the performance of banks.
Data
This analysis uses the Consolidated Reports of
Condition and Income (Call Reports) data. The
sample consists of domestically chartered, FDICinsured commercial banks. The sample excludes
banks that were less than five years old at the
22 Potential biases resulting from the exclusion of merged
banks will be discussed below.
23 For example, the act authorizes federal banking regulators
to limit the growth of an institution and to remove any person
causing harm to an insured financial institution.
time of financial statements, and banks that were
involved in mergers and acquisitions during the
year analyzed. Relatively new banks may behave
unusually. For example, they may expand rapidly
despite low profits to cultivate a customer base.
Mergers and acquisitions can dramatically change
the financial characteristics of banks involved.22
In these cases, risk-taking may not have much to
do with changed financial characteristics.
The time span covered by this analysis is 1984
to 1988. Changes in risk measures during 1985,
1986, 1987 and 1988 are examined based on
capital ratios and earnings on assets at the end
of 1984, 1985, 1986 and 1987, respectively. The
deregulation of the early 1980s, which under
mined the charter values of banks and opened
more risk-taking opportunities for them, might
have led to active risk-taking in the mid-1980s.
Legislative changes in the late 1980s discouraged
banks from taking risk. The Federal Reserve
Board introduced risk-based capital guidelines
in 1988 based on the 1987 Basle Accord, and
the Financial Institutions Reform, Recovery
and Enforcement Act of 1989 tightened bank
and thrift regulation.23 The FDIC Improvement
Act of 1991 added more provisions designed to
prevent risk-taking, such as risk-based deposit
insurance premiums, prompt corrective action
on undercapitalized banks, and more frequent
bank examinations. Thus, risk-taking is likely to
have been most active during the years examined
by this study.
Capital Ratios
Banks are divided into four groups based on
the year-end ratio of capital to assets: Group
C l—less than 5 percent; Group C2—greater than
or equal to 5 percent but less than 7 percent;
Group C3—greater than or equal to 7 percent
but less than 10 percent; and Group C4—greater
than or equal to 10 percent.24 According to moral
hazard theories, the first group has the strongest
incentive to take risk and the incentive decreases
with the capital ratio. The incentive, however,
may not translate into actual risk-taking because
of regulatory constraints. The capital ratios of
since the stock market data are not available for most small
banks. The book value may differ from the market value.
The difference, however, may introduce merely a random
noise rather than a systematic bias.
24 This analysis uses the book value of equity capital, consist
ing of common stock, perpetual preferred stock, surplus and
retained earnings. The market value cannot be obtained,
JULY/AUGUST 1994
10
most banks in the first group fall short of the
required minimum.25 Thus, banks in the first
group may have been subjected to tight supervi
sion by regulators and unable to increase risk.
Most aggressive risk-taking by the second group,
therefore, is also consistent with the moral
hazard theory.
Risk measures used here include: the rate of loan
growth; the change in the ratio of commercial
real estate loans (loans secured by construction
and land development, multifamily residential
properties and nonfarm, nonresidential properties)
to total loans; the change in the ratio of loans to
insiders (executive officers and principal share
holders) to total loans; the change in the ratio of
large time deposits (time deposits of $100,000 or
more) to total assets; and the interest rate on
large time deposits.26 Since sound investment
opportunities are limited, rapid loan growth
generally increases the risk of banks. Commercial
real estate loans are regarded as relatively risky
loans, and some banks may apply lower lending
standards to insiders. Thus, the riskiness of loan
portfolios may increase with the proportions of
commercial real estate loans and loans to insiders.
Increases in the share of large time deposits and
high interest rates on large time deposits may
indicate the banks’ desire to expand rapidly and
to take risk. Bidding up interest rates on large time
deposits is a fast way to raise funds for rapid
expansion because large time deposits are more
sensitive to interest rates than other deposits.
In comparing risk-taking behavior across the
four groups, this analysis focuses mainly on
the distribution of percentile ranks of each risk
measure. The use of percentile ranks, instead
of actual values, makes the analysis concise.
Examination of the distribution, rather than
summary statistics, enables more comprehensive
analyses of bank behavior. Furthermore, summary
statistics of ratios or growth rates can be seriously
contaminated by outliers. This analysis some
what sacrifices analytical rigor in that it does not
rely on formal statistical tests. The lack of formal
statistical tests may, however, be partly compen
25 The minimum ratio of primary capital to total assets was set
at 5.5 percent in 1985 and remained in effect until the end of
1990. Primary capital includes loan-loss provisions. Risktaking incentives may be more closely related to stockhold
ers’ equity than primary capital.
26 The interest rate is estimated by dividing interest expense
on time certificates of deposit of $100,000 or more by the
average amount of the same deposit outstanding during the
year.
Digitized forFEDERAL
FRASER RESERVE BANK OF ST. LOUIS
sated by the fact that the entire population of
commercial banks is examined over an extensive
time period.
Table 1 presents summary statistics and a con
densed distribution of the percentile rank of loan
growth, in which higher percentiles are associated
with higher rates of loan growth. The table shows
the lowest median rate of loan growth for Group
C l banks in all four years, but fails to show any
apparent pattern among the remaining three
groups. Although Group C2 generally had high
median rates of loan growth, the group with the
highest median differs across years. Thus, com
parison of median loan growth rates fails to
present clear evidence of moral hazard.
The distribution of loan growth is more inter
esting. The table reports the percentage of banks
in each group belonging in a certain percentile
rank group of the entire population. For example,
28.6 percent of Group C l banks in 1984 had
loan growth rates ranking them in the 0-10 per
centile in 1985. Thus, the proportion of Group
C l banks belonging in the 0-10 percentile group
was almost three times as large as that of the
entire population of banks. If the distribution
of a group is roughly equal to the distribution
of the entire population, about 10 percent of
the group should belong in the 0-10 percentile
group, another 10 percent in the 10-20 percentile
group, about 30 percent in the 20-50 percentile
group, and so on.
Many Group C l and Group C2 banks grew very
slowly (0-10 percentile ranks), while many other
banks in the same groups grew very fast (90-100
percentile ranks). In contrast, well-capitalized
banks belonged mostly in the middle percentile
groups (20-50 percentile ranks and 50-80 per
centile ranks). In 1987 and 1988, the proportion
of Group C l banks belonging in the 90-100 per
cent group decreased markedly, but remained
larger than the proportion in the 80-90 per
centile group. A possibility is that regulators
more successfully prevented undercapitalized
banks from expanding loans in those years, but
that some undercapitalized banks continued to
11
Table 2
Changes in the Ratio of Commercial Real
Estate Loans to Total Loans
Table 1
Rates of Loan Growth
1984-1985
Percentile
0-10
10-20
C1
C2
28.6%
11.9
10.3%
8.0
C3
8.6%
10.0
1984-1985
C4
10.7%
Percentile
C1
C2
13.5%
C3
12.5%
9.2%
C4
12.3
0-10
9.1
10.7
10.5
8.1
8.5%
20-50
19.8
22.9
32.6
33.7
10-20
50-80
16.7
31.9
31.0
26.8
20-50
20.7
24.2
30.4
37.0
80-90
10.7
12.7
9.5
7.7
50-80
29.0
28.4
30.9
30.2
90-100
12.3
14.0
8.4
8.5
80-90
11.6
11.7
9.4
9.1
Number of banks
318
3,190
6,224
2,620
90-100
16.0
12.5
9.6
7.1
Mean
0.0074
0.0832
0.0577
0.0548
Number of banks
318
3,190
6,224
2,620
-0.0104
0.0782
0.0434
0.0249
Mean
0.0129
0.0092
0.0073
0.0049
Median
0.0052
0.0031
0.0011
0.0000
Percentile
C1
Median
1985-1986
Percentile
C2
C1
11.6%
C3
8.4%
1985-1986
C4
7.9%
0-10
34.5%
10-20
12.6
9.6
9.6
11.0
0-10
20-50
20.3
24.5
31.6
34.5
50-80
16.8
29.4
31.4
80-90
4.7
11.4
10.3
90-100
11.1
13.4
Number of banks
380
3,119
Mean
-0.0276
0.0598
0.0449
Median
-0.0777
0.0484
0.0299
Percentile
10-20
C1
C2
34.8%
16.5
12.6%
9.6
C3
C4
10.5%
10.1%
10-20
7.9
9.7
9.9
10.9
29.5
20-50
25.5
23.1
29.9
39.2
8.4
50-80
25.7
30.6
31.1
27.4
8.8
8.7
80-90
14.5
12.7
9.4
7.4
6,050
2,541
90-100
15.5
13.2
9.6
6.2
0.0608
Number of banks
380
3,119
6,050
2,541
0.0179
Mean
0.0215
0.0176
0.0122
0.0065
Median
0.0113
0.0102
0.0047
0.0000
Percentile
C1
1986-1987
0-10
C2
10.8%
C3
7.2%
9.4
1986-1987
C4
7.1%
9.0%
C2
C3
9.4%
C4
10.4
0-10
11.1%
11.4%
10.7
10.2
10.2
9.2
9.2%
20-50
22.3
27.5
31.0
32.9
10-20
50-80
12.6
27.6
32.7
31.0
20-50
25.5
25.1
29.7
38.1
80-90
6.2
11.2
9.6
10.3
50-80
24.6
29.2
31.4
29.2
90-100
7.6
11.5
10.1
8.4
80-90
11.4
11.4
10.2
7.4
Number of banks
552
3,048
5,597
2,370
90-100
16.7
12.8
9.1
6.9
Mean
-0.0305
0.0648
0.0757
0.3530
Number of banks
552
3,048
5,597
2,370
Median
-0.0616
0.0523
0.0579
0.0492
Mean
0.0170
0.0128
0.0092
0.0048
Median
0.0050
0.0054
0.0034
0.0000
Percentile
C1
1987-1988
Percentile
0-10
C1
38.0%
C2
11.4%
C3
7.5%
1987-1988
C4
8.1%
10-20
15.7
10.1
9.4
10.0
20-50
20.4
27.6
31.6
30.8
0-10
16.3%
C2
C3
10.7%
9.9%
C4
8.2%
10-20
10.4
8.6
10.3
10.7
20-50
22.6
25.6
30.1
35.7
50-80
15.0
29.5
31.4
30.6
80-90
3.8
9.9
10.7
9.8
50-80
26.7
31.1
30.0
29.5
10.6
12.2
9.8
8.0
90-100
7.1
11.5
9.3
10.7
80-90
2,550
5,557
2,526
Number of banks
521
Mean
-0.0170
Median
-0.0356
90-100
13.4
11.8
9.8
8.0
0.0811
0.0874
0.1532
Number of banks
521
2,550
5,557
2,526
0.0766
0.0774
0.0779
Mean
0.0061
0.0089
0.0055
0.0045
Median
0.0007
0.0035
0.0002
0.0000
Notes: Group C1: Capital Ratio < 0.05; Group C2: 0.05 < Capital
Ratio < 0.07; Group C3: 0.07 < Capital Ratio <0.10; and Group
C4: Capital Ratio >0.10.
JULY/AUGUST 1994
12
grow extremely fast when they could circumvent
supervision. The rapid loan growth of many
poorly capitalized banks may have been moti
vated by moral hazard.
deposit at risky banks (supply). Nevertheless,
the pattern of changes in the ratio of large
deposits appears to be consistent with those
of loan growth and shifts in loan portfolios.
Tables 2 and 3 show changes in the ratio of
commercial real estate loans to total loans, and
changes in the ratio of loans to insiders to total
loans. The changes in the ratio of commercial
real estate loans display patterns similar to the
rates of loan growth. W hile the ratio fell sharply
for many Group C l and Group C2 banks, it
increased significantly for many others. Group
C3 and Group C4 banks were concentrated in
the middle percentile groups. The ratio for
Group C l banks in the highest percentile, how
ever, did not decrease substantially in 1987 and
1988, unlike the rate of loan growth. In addi
tion, the median change was inversely related
to the capital ratio. These results may reflect
the difficulty of regulating the riskiness of loan
portfolios, compared with restricting the rate of
loan expansion. In the case of loans to insiders,
only Group C l banks were distributed heavily
toward both tails. It appears that only those
banks facing the possibility of imminent failure
relied on insider loans as a means of increasing
risk. The median fails to show a clear pattern.
In sum, the average behavior of poorly capital
ized banks was not notably different from that
of well-capitalized banks. A more interesting
finding is that a higher proportion of low-capital
banks adopted highly risky strategies. This effect
might have been more pronounced if the behavior
of banks that failed during the year were included
in the sample. Failed banks, most of which had
been poorly capitalized, might have pursued
extremely risky strategies if they were given
the opportunity.27
In general, large time deposits appear to have
grown slower at poorly capitalized banks. Table 4
shows smaller changes in the ratio of large time
deposits to total assets for many Group C l and
Group C2 banks. A sizable proportion of group
C2 banks, however, showed relatively fast
increases in the ratio. Furthermore, although
a relatively small proportion of Group C l banks
belonged in the 90-100 percentile groups, the
proportion was consistently higher than that
belonging in the 80-90 percentile group.
Poorly capitalized banks generally paid higher
interest rates on large time deposits, but the
interest rates were not distributed heavily toward
the tails (Table 5). It is complicated to interpret
the behavior of large time deposits, which are
not fully insured, and the interest rates on those
deposits because demand and supply factors
interact. In other words, the two variables reflect
both the desire of low-capital banks to grow
(demand) and the willingness of investors to
27 Failed banks include FDIC-assisted mergers. Another
source of potential bias is voluntary mergers. The proportion
of poorly capitalized banks (Groups C1 and C2), however,
was not significantly higher than the proportion of well-capi
talized banks (Groups C3 and C4) among acquired banks.
Digitized forFEDERAL
FRASER RESERVE BANK OF ST. LOUIS
Earnings on Assets
This section compares four groups of banks,
representing each quartile of earnings on assets;
Group E l and Group E4 represent the lowest and
highest quartiles. Managers of Group E l banks,
who were incompetent or had bad luck, may
have had the strongest incentives to increase
risk because they needed high earnings in the
next period to preserve their jobs. Thus, the
theory based on the managers’ incentives pre
dicts the most aggressive risk-taking by Group
E l banks and the most conservative strategies
by Group E4 banks.
The same risk measures used in the previous
section are analyzed. Table 6 shows a positive
relationship between earnings on assets and
the rate of loan growth. The median growth
rate w as g enerally high er for banks with higher
earnings. This result suggests that the availability
of profitable investment opportunities was the
main determinant for loan growth; banks with
high earnings, which might have more profitable
lending opportunities, grew faster. A notable
pattern in the table, however, is that the propor
tion of Group E l banks belonging in the 90-100
percentile group consistently exceeded that
belonging in the 80-90 percentile group. It is
thus possible that the pattern of loan growth
reflected the desperate attempts of some bank
managers to increase profits.
The pattern of changes in loan portfolios
for low-earnings banks is similar to that for
13
Table 4
Changes in the Ratio of Large Time
Deposits to Assets
Table 3
Changes in the Ratio of Loans to
Insiders to Total Loans
1984-1985
1984-1985
Percentile
0-10
10-20
C2
C1
16.0%
10.0%
8.0
9.9
C3
C4
Percentile
C2
C1
03
8.4%
C4
6.1%
10.7%
0-10
27.7%
14.4%
10.0
10.4
10-20
13.5
12.0
10.2
6.8
28.7
20-50
26.4
28.4
29.7
33.3
9.4%
20-50
26.2
30.1
30.7
50-80
29.8
31.4
30.0
28.2
50-80
16.4
26.5
31.6
32.0
80-90
7.6
9.1
10.4
10.6
80-90
6.9
8.9
10.1
11.5
90-100
12.4
9.6
9.5
11.4
90-100
9.1
9.8
10.1
10.2
2,758
5,379
2,015
Number of banks
318
3,190
6,224
2,620
Number of banks
275
Mean
-0.00027
0.00010
-0.00006
0.00088
Mean
-0.0184
-0.0038
0.0018
0.0049
Median
-0.00001
-0.00001
-0.00001
0.00000
Median
-0.0128
-0.0024
0.0008
0.0019
Percentile
C1
C4
Percentile
C1
1985-1986
1985-1986
C2
C3
C2
C3
C4
0-10
29.5%
12.6%
9.1%
6.1%
9.9
10-20
11.8
12.9
9.6
7.0
29.5
29.0
20-50
26.6
29.8
31.2
28.2
9.2%
15.8%
10.2%
10-20
9.7
8.3
10.9
20-50
23.5
32.4
0-10
10.7%
50-80
27.8
31.7
30.4
27.0
50-80
17.9
25.2
30.2
37.2
80-90
10.6
8.5
9.9
12.3
80-90
6.3
8.6
10.1
11.9
90-100
12.6
8.9
10.0
11.1
90-100
7.9
11.1
9.8
9.6
Number of banks
341
2,665
5,276
1,952
Number of banks
380
3,119
6,050
2,541
Mean
0.00042
-0.00060
Median
0.00000
-0.00002
Percentile
C1
Mean
-0.0256
-0.0058
-0.0039
0.0006
0.00000
Median
-0.0177
-0.0061
-0.0031
-0.0002
C4
Percentile
C1
9.0%
0-10
22.6%
12.4%
8.7%
6.9%
0.00049 -0.00003
-0.00001
1986-1987
1986-1987
C2
C3
C2
C3
C4
0-10
14.7%
9.8%
10.0%
10-20
10.6
8.5
10.2
11.3
10-20
10.7
10.4
9.9
9.4
20-50
23.8
30.7
30.1
30.3
20-50
26.2
24.4
30.5
37.2
50-80
30.9
33.7
29.2
26.7
50-80
20.8
29.0
31.1
31.0
80-90
8.9
8.7
10.5
10.7
80-90
6.9
11.1
10.3
8.6
90-100
11.0
8.5
9.9
11.9
90-100
12.9
12.6
9.5
7.0
Number of banks
462
2,565
4,883
1,836
Number of banks
552
3,048
5,597
2,370
Mean
-0.00046
-0.00045
Mean
-0.0027
0.0030
0.0038
0.0029
Median
-0.00002
-0.00002
Median
-0.0017
0.0033
0.0024
0.0004
0.00017
0.00080
-0.00004 -0.00006
1987-1988
1987-1988
Percentile
C1
C2
Percentile
C1
C2
C3
C4
29.0%
12.8%
8.4%
6.5%
10.1
10.3
10-20
13.1
12.0
9.8
7.7
27.8
31.2
32.0
20-50
23.7
26.6
29.9
35.1
31.0
33.7
29.9
26.0
50-80
18.7
27.3
31.5
31.9
9.0
10.0
9.8
10.5
80-90
7.1
10.5
10.3
9.6
13.3
9.9
9.5
10.7
90-100
8.3
10.7
10.2
Number of banks
521
2,550
5,557
Mean
-0.0130
0.0022
0.0052
0.0066
Median
-0.0062
0.0029
0.0044
0.0040
9.8%
10-20
13.6
8.8
20-50
19.5
50-80
80-90
2,202
Number of banks
435
Mean
-0.00133
0.00044
Median
-0.00005
-0.00004
C4
0-10
13.6%
90-100
03
10.4%
0-10
9.6%
4,858
-0.00021
1,944
0.00001
-0.00015 -0.00025
9.3
2,526
JULY/AUGUST 1994
14
Table 5
Interest Rates on Large Time Deposits
Table 6
Rates of Loan Growth
1984-1985
1985
Percentile
C1
C2
0-10
7.7%
7.9%
10.1%
12.8%
0-10
21.4%
6.7%
5.3%
10-20
8.0
8.6
10.3
11.3
10-20
15.5
8.1
7.7
8.8
20-50
27.6
34.4
29.6
25.6
20-50
30.5
29.7
28.7
31.1
50-80
32.8
32.1
30.0
26.9
50-80
19.2
34.0
35.2
31.7
80-90
12.2
9.1
10.0
11.0
80-90
6.2
10.9
12.1
10.8
90-100
11.6
8.0
10.0
12.4
90-100
7.3
10.7
11.1
10.9
Number of banks
311
3,143
6,014
2,360
Number of banks
3,056
3,082
3,104
3,113
Mean
0.0882
0.0871
0.0871
0.0868
Mean
Median
0.0876
0.0861
0.0863
0.0864
Median
Percentile
C1
C4
Percentile
C3
C4
Percentile
E1
0-10
7.4%
8.5%
E3
E4
6.8%
0.0059
0.0770
0.0835
0.0824
-0.0148
0.0613
0.0721
0.0565
1985-1986
1986
C2
E2
C3
10.1%
E1
E2
E3
E4
13.5%
0-10
23.8%
7.3%
4.7%
4.7%
17.4
9.0
6.8
7.2
7.9
9.0
10.2
11.3
10-20
20-50
23.5
33.9
29.8
26.6
20-50
32.0
31.9
27.9
28.3
50-80
35.9
31.8
29.7
27.6
50-80
16.4
31.4
35.6
36.1
9.9
80-90
4.6
10.0
13.1
12.1
5.8
10.3
12.0
11.6
2,945
3,036
3,057
3,062
10-20
80-90
10.4
9.3
90-100
13.7
8.5
Number of banks
365
3,067
Mean
0.0747
Median
0.0745
0.0736
0.0725
10.4
10.0
11.2
90-100
5,846
2,333
Number of banks
0.0733
0.0725
0.0726
Mean
-0.0178
0.0541
0.0781
0.0819
0.0723
Median
-0.0591
0.0354
0.0615
0.0611
1986-1987
1987
Percentile
C1
C2
0-10
9.7%
7.6%
10-20
9.8
8.1
C3
10.2%
9.9
C4
12.8%
12.8
20-50
24.1
28.5
31.2
30.4
50-80
34.8
35.8
28.9
23.6
80-90
9.8
10.5
9.8
9.9
90-100
11.8
9.5
Number of banks
518
Mean
0.0650
Median
2,968
0.0658
0.0654
0.0654
9.9
5,407
0.0643
0.0643
10.5
2,180
0.0634
0.0633
0-10
C1
C2
8.6%
7.1%
C3
10.0%
C4
13.3%
10-20
10.0
7.4
9.5
13.9
20-50
25.8
26.7
30.7
32.7
50-80
80-90
32.6
12.6
36.2
12.1
30.4
9.7
22.0
7.9
90-100
10.6
10.5
9.6
10.3
Number of banks
501
2,492
5,419
2,357
Mean
0.0700
Median
0.0713
0.0711
0.0717
E1
E2
E3
E4
4.1%
0-10
25.6%
7.2%
4.3%
10-20
18.1
9.1
7.3
6.2
20-50
30.7
33.4
29.0
26.8
50-80
15.1
31.0
35.3
37.5
80-90
4.3
9.5
12.7
13.0
90-100
6.2
9.7
11.4
12.3
2,722
2,924
2,956
2,975
Number of banks
Mean
Median
0.2278
0.0720
0.0911
0.1143
-0.0375
0.0521
0.0767
0.0863
1987-1988
1988
Percentile
Percentile
0.0698
0.0703
Digitized forFEDERAL
FRASER RESERVE BANK OF ST. LOUIS
0.0684
0.0685
Percentile
E1
E2
E3
E4
0-10
25.4%
8.0%
3.8%
4.1%
10-20
16.0
9.7
7.9
6.9
20-50
28.2
32.7
30.8
28.2
50-80
16.8
29.6
35.3
36.9
80-90
4.8
10.2
12.2
12.4
90-100
8.7
9.6
10.0
11.5
2,603
2,845
2,838
2,878
Number of banks
Mean
0.0379
0.0852
0.1045
0.1498
Median
0.0011
0.0727
0.0916
0.1016
Notes: Each group represents a quartile of earnings on assets.
During the four years, the cutoff points were about 0.005 between
Groups E1 and E2, 0.011 between Groups E2 and E3, and 0.016
between Groups E3 and E4.
15
low-capital banks but somewhat less pronounced.
While many Group E l banks reduced the ratios
of commercial real estate loans and loans to
insiders to total loans, a large proportion of banks
in the same group rapidly increased the portfolio
shares of the risky loans (Tables 7 and 8). No
apparent pattern is found for other groups. These
findings suggest that a higher proportion of lowearnings banks pursued highly risky strategies.
The ratio of large time deposits to assets
increased faster for banks with higher earnings
(Table 9). Yet a sizable proportion of Group E l
banks increased the ratio of large time deposits
very fast (90-100 percentile ranks). In addition,
a relatively high proportion of Group E l banks
paid the highest interest rates on large time
deposits (Table 10). Thus, many Group E l
banks appear to have bid up interest rates
to attract large time deposits.
Examination of the effects of earnings on
risk-taking presents findings similar to the ones
derived from the relationship between capital
adequacy and risk-taking behavior. Although
the majority of banks with low earnings were
comparatively conservative, many other banks
with low earnings adopted extremely risky
strategies. As in the case of low-capital banks,
this result could have been strengthened if the
behavior of banks that failed during the year
were taken into consideration.28 The divergent
risk-taking behavior among low-earnings banks,
however, is not as pronounced as that among
low-capital banks. Thus, although this analysis
supports the hypothesis that low earnings
induced some banks to increase risk aggressively,
evidence is somewhat weaker than that for moral
hazard. In addition, the true motivation for risktaking is not clear for some low-earnings banks
because many low-earnings banks also had low
capital.29 This problem will be addressed below.
28 The majority of failed banks belonged in Group E1. Among
acquired banks, the proportion of Group E1 banks was the
highest in three of the four years. The proportion, however,
was not overwhelming.
Conditions o f Local Economies
If external shocks are the main factor affecting
the condition of banks, the strength of local
economies should largely explain behavior and
performance differences across banks. Table 11
shows the results of two sets of regressions that
examine the effects of employment growth in
home states on earnings on assets and loan growth.
The employment growth, which reflects the con
dition of local economies, is found to positively
affect earnings and loan growth. Although they
support the significance of local economic con
ditions, these results do not disprove the roles
of other factors.
We may better assess the roles of stockholders’
and managers’ incentives by examining whether
the behavior of banks that cannot be explained
by the condition of local economies is systemati
cally related to capital ratios or earnings on assets
of the previous period. Thus, the residual rates
of loan growth are examined.30 Higher demand
for bank loans generally follows improving eco
nomic conditions. Thus, the residuals reflect
the loan growth that is unexplained by demand
effects. Systematic differences in the residual
loan growth across groups may be viewed as
consequences of risk-taking in previous periods.
Tables 12 and 13 report the distribution of the
residual rates of loan growth. The distribution
of the residuals is similar to that of loan growth
observed in Tables 1 and 6. Group C2 banks
are distributed heavily toward both tails. For
Group C l and E l banks, the percentage of banks
belonging in the highest percentile group is not
high, but consistently higher than that in the
second highest percentile group. Thus, after
considering the condition of local economies,
systematic differences still exist in loan growth
across the groups classified based on capital
ratios and earnings on assets. Accordingly, the
recognition of large loan loss provisions by banks with lowquality loans. For this reason, the residual changes in earn
ings are not discussed in detail.
29 The correlation coefficient between capital ratios and earn
ings on assets was 0.393 in 1984, 0.326 in 1985, 0.335 in
1986, and 0.432 in 1987. The correlation may become even
higher if the market value, instead of book value, of capital is
used. Banks with high-quality assets are more likely to have
high earnings and high market values relative to book values.
30 The residual changes in earnings for low-capital and lowearnings banks are found to be distributed heavily toward
both tails. It is possible to interpret large variances in earn
ings changes as a result of risk-taking in previous periods.
The large variances, however, can result from delayed
JULY/AUGUST 1994
16
Table 7
Changes in the Ratio of Real Estate
Loans to Total Loans
Table 8
Changes in the Ratio of Loans to Insiders
to Total Loans
1984-1985
Percentile
0-10
E1
E2
12.4%
9.3%
1984-1985
E3
8.8%
E4
Percentile
9.5%
0-10
E1
E2
13.1%
8.9%
E3
7.6%
E4
10.5%
10-20
10.0
10.9
10.6
8.5
10-20
10.2
9.2
9.7
10.9
20-50
28.2
29.2
31.6
31.0
20-50
25.0
31.4
32.7
30.8
50-80
28.9
30.6
29.5
31.2
50-80
27.9
31.7
31.9
28.3
80-90
9.8
10.7
9.9
9.6
80-90
11.9
9.4
8.9
9.8
90-100
10.7
9.5
9.5
10.2
90-100
11.9
9.2
9.2
9.7
Number of banks
3,056
3,082
3,104
3,113
Number of banks
2,641
2,694
2,630
2,465
Mean
0.0065
0.0078
0.0075
0.0079
Mean
0.00024
-0.00019
0.00058 -0.00001
Median
0.0010
0.0016
0.0009
0.0018
Median
0.00003
0.00000
-0.00001 -0.00007
1985-1986
Percentile
0-10
E1
E2
10.0%
9.8%
1985-1986
E3
9.7%
E4
10.5%
Percentile
0-10
E1
E2
13.3%
9.4%
E3
8.6%
E4
8.7%
10-20
9.6
10.4
9.7
10.2
10-20
9.1
10.6
9.1
11.3
20-50
30.2
30.2
29.4
30.0
20-50
26.3
30.2
31.9
31.6
50-80
29.2
29.8
30.1
30.8
50-80
29.6
29.9
31.8
28.8
80-90
10.2
10.0
10.7
9.1
80-90
10.3
10.0
9.7
10.0
90-100
10.9
9.7
10.1
9.4
90-100
11.5
10.0
9.0
9.6
Number of banks
2,945
3,036
Number of banks
2,497
2,626
2,654
2,462
3,057
3,062
Mean
0.0135
0.0122
0.0130
0.0122
Mean
Median
0.0048
0.0046
0.0055
0.0043
Median
-0.00070
0.00043
0.00001
-0.00001
1986-1987
Percentile
E1
E2
0.00029
0.00000 -0.00006
1986-1987
E4
Percentile
9.0%
9.0%
0-10
9.7
10-20
9.9
E3
0-10
12.2%
10-20
10.9
9.8
9.6
20-50
28.8
29.9
30.3
30.8
20-50
5 -8 0
28.3
31.3
30.6
29.7
50-80
80-90
10.0%
0.00037
E1
E2
12.5%
10.0%
E3
8.6%
E4
9.0%
10.0
10.4
9.6
25.2
29.5
31.8
33.1
28.1
31.0
30.9
29.7
9.0
8.7
9.4
11.4
10.4
80-90
11.6
10.2
9.4
90-100
10.9
9.6
9.1
10.4
90-100
12.6
9.2
8.8
9.6
Number of banks
2,722
2,924
2,956
2,975
Number of banks
2,263
2,500
2,536
2,457
Mean
0.0081
0.0096
0.0102
0.0106
Mean
-0.00014
-0.00005
Median
0.0018
0.0032
0.0036
0.0032
Median
0.00003
-0.00002
Percentile
E1
E4
Percentile
E1
8.7%
1987-1988
E2
0.00024
0.00034
-0.00006 -0.00008
1987-1988
E3
E2
E3
E4
0-10
13.3%
10.0%
8.2%
0-10
13.0%
10-20
10.2
10.2
9.8
9.8
10-20
11.2
10.3
9.6
9.0
20-50
28.9
30.4
30.7
29.9
20-50
23.5
30.2
32.8
32.8
50-80
26.5
30.1
32.3
30.8
50-80
28.0
28.2
31.9
31.8
80-90
11.0
11.4
9.1
8.6
90-100
13.4
10.2
8.1
Number of banks
2,196
2,429
9.4
9.9
9.5
11.1
90-100
11.7
9.3
9.4
9.7
Number of banks
2,603
2,845
2,838
2,878
80-90
Mean
0.0046
0.0056
0.0068
0.0071
Mean
Median
0.0000
0.0000
0.0009
0.0013
Median
Digitized forFEDERAL
FRASER RESERVE BANK OF ST. LOUIS
9.8%
8.3%
2,462
9.2%
8.6
2,360
0.00021
-0.00001
-0.00014 -0.00031
-0.00005
-0.00014
-0.00015 -0.00015
17
Table 10
Interest Rates on Large Time Deposits
Table 9
Changes in the Ratio of Large Time
Deposits to Assets
1984-1985
1984-1985
E1
Percentile
E2
16.4%
0-10
8.7%
E3
7.8%
Percentile
E1
E2
E4
0-10
9.4%
8.8%
E3
7.2%
10-20
8.9
10.5
10.4%
9.9
E4
11.4%
10.7
10-20
12.8
9.5
8.9
8.9
20-50
27.8
32.7
30.0
29.5
20-50
29.6
30.1
30.7
29.8
50-80
30.9
29.4
31.1
28.6
50-80
24.7
31.2
32.3
31.5
80-90
10.8
10.0
9.9
9.3
80-90
7.5
10.4
10.9
11.2
90-100
12.2
8.5
8.7
10.6
2,928
2,991
3,013
2,899
90-100
Number of banks
9.1
10.1
9.5
11.3
Number of banks
3,056
3,082
3,104
3,113
Mean
0.0886
0.0867
0.0864
0.0865
Median
0.0873
0.0859
0.0862
0.0860
Mean
-0.0064
0.0017
0.0022
0.0043
Median
-0.0038
0.0009
0.0011
0.0021
1985-1986
1985-1986
E1
Percentile
E2
0-10
17.6%
10-20
11.8
8.8%
E3
E4
Percentile
E1
0-10
9.5%
E2
E3
10.1%
9.2%
E4
11.2%
7.3%
6.6%
10-20
9.8
9.9
10.1
10.2
11.2
9.3
7.7
20-50
28.0
31.0
31.1
29.8
29.8
30.4
30.4
29.3
10.0
20-50
28.5
32.4
31.3
27.9
50-80
50-80
25.0
28.8
31.7
34.2
80-90
10.4
9.6
10.0
80-90
8.3
9.5
10.3
11.9
90-100
12.5
8.9
9.2
9.5
90-100
8.8
9.2
10.1
11.9
Number of banks
2,804
2,948
2,972
2,896
2,945
3,036
3,057
3,062
Mean
0.0745
0.0728
0.0731
0.0728
Median
0.0732
0.0723
0.0725
0.0723
Percentile
E1
Number of banks
Mean
-0.0123
-0.0044
-0.0021
0.0020
Median
-0.0078
-0.0045
-0.0022
-0.0001
1986-1987
1986-1987
E1
Percentile
E2
E3
E4
0-10
17.2%
10.5%
6.3%
6.6%
10-20
12.6
10.3
8.9
8.4
20-50
30.7
29.1
29.7
30.6
50-80
23.1
29.4
33.4
33.4
80-90
6.8
10.1
11.2
11.7
90-100
9.7
10.5
10.6
9.2
2,722
2,924
2,956
Number of banks
2,975
Mean
-0.0035
0.0031
0.0068
0.0052
Median
-0.0010
0.0020
0.0042
0.0039
0-10
E1
0-10
19.2%
13.5
10-20
E2
8.9%
10.4
E3
6.6%
8.3
E4
6.2%
8.1
27.4
31.7
30.0
30.6
50-80
22.4
29.4
34.7
32.7
7.5
10.8
11.8
9.9
9.8
9.7
10.6
2,603
2,845
2,838
2,878
90-100
Number of banks
9.6
Mean
Median
-0.0036
-0.0004
0.0039
0.0033
9.2%
E4
10.5%
10-20
11.3
9.9
9.5
9.4
29.5
30.1
29.8
30.7
50-80
29.6
30.3
30.3
29.8
80-90
9.0
9.5
10.8
10.6
90-100
10.5
10.2
10.4
Number of banks
2,557
2,797
2,863
9.0
2,866
Mean
0.0644
0.0644
0.0649
0.0641
Median
0.0643
0.0645
0.0649
0.0645
Percentile
E1
1987-1988
20-50
80-90
E3
10.1%
20-50
1987-1988
Percentile
E2
10.2%
0.0068
0.0059
0.0079
0.0057
E3
E4
10.5%
9.4%
10-20
10.8
10.6
8.9
9.8
20-50
30.5
30.8
30.0
28.8
50-80
29.8
28.6
31.6
30.1
80-90
9.7
9.3
10.2
10.7
90-100
9.8
10.1
10.0
10.0
2,487
2,742
2,763
2,786
0-10
Number of banks
9.4%
E2
10.6%
Mean
0.0697
0.0696
0.0702
0.0696
Median
0.0702
0.0700
0.0707
0.0705
JULY/AUGUST 1994
18
finding that local economic conditions were an
important explanation of the performance of
banks does not deny the roles of the risk-taking
incentives of stockholders and managers.
Ch aracteristics o f Risk- Takers
We may better understand the motives for
risk-taking by looking at other characteristics
of the low-capital and low-earnings banks that
took high risks. This section examines more
closely the Groups C l, C2 and E l banks that
belonged in the 90-100 percentile group in
loan growth (defined as “risky banks”).
The positive correlation between capital ratios
and earnings mentioned above suggests the pos
sibility that the risky low-capital (Groups C l and
C2) banks may also be low-earnings banks (Group
E l). Then, the above analyses cannot distinguish
between stockholders’ and managers’ incentives.
Table 14 classifies risky low-capital banks based
on earnings and risky low-earnings banks based
on capital ratios. In general, the percentage of
risky low-capital banks belonging in Group E l
was no higher than that of the entire population
of banks. Compared with the composition of
the population, a higher proportion of risky lowearnings banks belonged in Group C l or C2. The
proportion, however, was less than 50 percent in
three of the four years. Thus, the overlap between
risky low-capital and low-earnings banks suggests
a more significant effect of moral hazard, but does
not appear to be large enough to invalidate inde
pendent roles of stockholders’ and managers’
incentives.
Some researchers argue that the “too-big-to-fail”
policy increased risk-taking incentives for large
banks because the policy further reduced the
expected loss to stockholders in the event of
insolvency and weakened market discipline by
uninsured depositors.31 Table 15 shows the size
distribution of risky banks with low capital or
low earnings. The percentage of the risky lowcapital banks with $5 billion or more in total
assets (Size 3 or Size 4) was no higher in general
than that of the population, and it was lower for
risky low-earnings banks. Thus, this analysis
does not support the too-big-to-fail hypothesis.
This result, of course, does not disprove the
hypothesis either. It may be difficult for large
banks, which already have significant market
shares, to expand rapidly. Thus, the selection
31 See Mishkin (1992) and Boyd and Gertler (1994).
Digitized for FEDERAL
FRASER RESERVE BANK OF ST. LOUIS
Table 11
Regression Results
(dependent variable: change in earnings on assets)
Intercept
1985
1986
1987
1988
-0.0031
-0.0038
-0.0004
-0.0013
(-12.44)
State*
0.0789
(8.49)
Adjusted
R-Square
0.0057
(-21.64)
0.1260
(16.17)
0.0211
(-1.69)
0.0532
(-2.19)
0.0731
(6.29)
(3.89)
0.0033
0.0013
(dependent variable: rate of loan growth)
Intercept
1985
1986
1987
1988
0.0083
0.0195
0.0222
0.0252
(2.04)
State*
2.5195
(16.34)
Adjusted
R-Square
0.0211
(4.44)
3.1992
(16.51)
0.0219
(0.27)
4.7001
(0.62)
2.2534
(1.67)
(1.78)
0.0002
0.0002
* State = Rate of employment growth in the home state.
Notes: Numbers in parenthesis are f-values. The statistical
significance of regressions fluctuates widely across years
mainly because of extreme values of dependent variables.
of the risk measure may be responsible for the
result. Nevertheless, it indicates that large
banks do not account for a large proportion of
those driven by risk-taking incentives.
Table 16 classifies risky banks based on holding
com p an y status in an attem p t to observe the rela
tionship between the ownership structure and
risk-taking. Compared with the composition of
the entire population, risky banks were more
likely to be owned by multi-bank holding com
panies, less likely to be owned by one-bank
holding companies, and about equally likely
to be independent. One possibility is that the
ownership share of managers is greatest for inde
pendent banks and smallest for banks owned by
multi-bank holding companies. Under this
assumption, the above finding suggests that
banks controlled by stockholders took more
risk, and, hence, supports the moral hazard
view. Another possibility is that stockholders
of multi-bank holding companies are least able
to monitor managers of member banks because
of the complicated organizational struct ure. In
19
Table 13
Residual Rates of Loan Growth
Table 12
Residual Rates of Loan Growth
1984-1985
1984-1985
Percentile
C2
C1
C3
04
Percentile
E1
E2
E3
E4
0-10
20.8%
12.1
10-20
15.4
8.9
7.6
8.3
32.1
32.4
20-50
30.0
30.0
29.4
30.6
30.3
31.5
27.9
50-80
19.7
32.6
34.7
33.0
12.6
9.7
7.6
80-90
6.4
11.4
12.1
10.0
10.7
13.2
8.6
9.2
90-100
7.8
10.4
10.8
11.0
3,190
6,224
2,620
3,056
3,082
3,104
3,113
0-10
28.6%
10-20
13.2
20-50
10.8%
8.3%
10.7%
8.6
9.7
22.6
24.6
50-80
14.4
80-90
10.4
90-100
Number of banks
6.8%
5.3%
7.2%
Number of banks
318
Mean
-0.0638
0.0137
-0.0021
-0.0038
Mean
-0.0520
0.0123
0.0201
0.0189
Median
-0.0841
0.0061
-0.0152
-0.0301
Median
-0.0717
-0.0009
0.0061
-0.0057
Percentile
C1
04
Percentile
8.8%
0-10
22.6%
8.2%
5.0%
4.7%
10-20
15.3
9.8
7.2
7.8
1985-1986
C2
11.5%
1985-1986
C3
8.4%
E1
E2
E3
E4
0-10
30.8%
10-20
14.7
9.1
9.9
10.6
20-50
20.5
26.8
30.9
33.1
20-50
30.1
30.1
30.0
29.8
50-80
17.2
28.5
31.6
30.0
50-80
19.7
31.6
33.7
34.6
80-90
7.1
11.3
10.2
8.3
80-90
5.1
10.6
11.8
12.2
90-100
9.7
12.8
8.9
9.2
90-100
7.0
9.7
12.2
11.0
Number of banks
380
3,119
6,050
2,541
2,945
3,036
3,057
3,062
Mean
-0.0673
0.0051
-0.0038
0.0135
Median
-0.0951
-0.0101
-0.0180
-0.0264
Number of banks
Mean
-0.0501
0.0017
0.0200
0.0266
Median
-0.0897
-0.0146
0.0033
0.0039
1986-1987
Percentile
0-10
C1
C2
27.9%
11.3%
1986-1987
C3
8.0%
04
Percentile
8.8%
0-10
E1
E2
21.1%
E3
8.1%
6.0%
E4
5.7%
10-20
13.9
10.3
9.5
9.8
10-20
14.0
10.8
8.2
7.3
20-50
25.8
28.1
31.1
31.0
20-50
26.8
31.1
31.0
30.8
50-80
18.2
29.8
31.5
29.8
50-80
22.3
29.8
34.6
32.7
80-90
6.7
10.1
10.2
10.3
80-90
6.6
10.2
10.6
12.3
90-100
7.6
10.6
9.8
10.3
90-100
9.1
10.0
9.7
11.1
Number of banks
552
3,048
5,597
2,370
2,722
2,924
2,956
2,975
Mean
-0.1272
-0.0614
-0.0518
0.2315
Median
-0.1466
-0.0759
-0.0731
-0.0761
Median
Percentile
C1
04
Percentile
7.9%
Number of banks
Mean
0.1395
-0.0554
-0.0481
-0.0254
-0.1269
-0.0776
-0.0625
-0.0581
1987-1988
C2
1987-1988
03
E1
E2
E3
E4
0-10
35.1%
0-10
24.7%
10-20
18.6
9.5
9.4
10.2
10-20
16.1
10.1
7.5
6.8
20-50
18.8
27.3
32.1
30.6
20-50
27.4
32.4
31.1
28.9
50-80
15.2
29.5
31.2
30.9
50-80
17.8
29.7
34.9
36.4
80-90
4.8
9.8
10.7
9.7
80-90
5.2
10.4
12.2
11.8
90-100
7.5
12.0
9.1
10.6
90-100
8.8
9.3
9.9
11.8
Number of banks
521
2,550
5,557
2,526
Number of banks
2,603
2,845
2,838
2,878
Mean
-0.1052
-0.0138
-0.0096
0.0577
Median
-0.1284
-0.0206
-0.0212
-0.0194
12.0%
7.6%
8.0%
4.3%
4.2%
Mean
-0.0531
-0.0114
0.0069
0.0525
Median
-0.0883
-0.0250
-0.0071
0.0029
JULY/AUGUST 1994
20
Table 14
Earnings on Assets and Capital Ratios of
Risky Banks
Table 15
Size Distribution of Risky Banks
1984
1984
Population
Population
Low capital
E1
E2
E3
E4
Total
3,064
3,083
3,106
3,113
12,366
(24.8%)
(24.9%)
(25.1%)
(25.2%)
107
178
135
(27.8%)
66
(22.0%)
(36.6%)
2,951
3,039
3,063
3,068
(24.3%)
(25.1%)
(25.3%)
(25.3%)
486
(13.6%)
Low capital
Size 1
Size 2
Size 3
Size 4
Total
11,736
576
45
9
12,366
(94.9%)
(4.7%)
408
(84.0%)
Low earnings
76
(15.6%)
204
19
(8.5%)
(91.5%)
1985
Population
Low capital
75
(16.3%)
154
(33.5%)
155
(33.7%)
76
Population
(16.5%)
Low capital
1986
Population
Low capital
2,734
2,928
2,960
2,982
(25.2%)
(25.5%)
(25.7%)
85
(21.7%)
115
(29.4%)
122
(31.2%)
69
11,604
Low capital
2,613
2,847
2,838
2,882
(25.5%)
(25.4%)
(25.8%)
104
(31.4%)
87
(26.3%)
Low earnings
59
81
(24.5%)
11,180
331
(17.8%)
Low capital
Low earnings
C2
C3
C4
Total
3,193
6,229
2,621
12,363
12
(5.4%)
95
(42.6%)
(50.4%)
(21.2%)
90
(40.4%)
26
223
Population
(11.7%)
1985
Low earnings
383
3,126
6,056
2,546
(25.8%)
(50.0%)
(21.0%)
17
58
(33.7%)
68
(39.5%)
29
12,111
Low earnings
5,606
2,376
(4.8%)
(26.3%)
(48.4%)
(20.5%)
62
(36.9%)
Low earnings
55
(32.7%)
28
2,554
5,559
2,529
(22.9%)
(49.8%)
(22.6%)
78
(34.5%)
(19.6%)
154
18
(0.4%)
4
(0.9%)
0
(0.0%)
(0.1%)
0
460
(0.0%)
0
172
(89.5%)
(10.5%)
(0.0%)
Size 1
Size 2
Size 3
Size 4
Total
10,935
609
51
9
11,604
(94.2%)
(5.2%)
341
48
(12.3%)
161
7
(4.2%)
(0.4%)
2
(0.5%)
0
(0.0%)
(0.1%)
0
391
(0.0%)
0
168
(0.0%)
Size 1
Size 2
Size 3
Size 4
Total
10,489
629
54
8
11,180
(93.8%)
(5.6%)
293
Low earnings
36
(10.9%)
214
12
(5.3%)
(0.5%)
2
(0.6%)
0
(0.0%)
(0.1%)
0
331
(0.0%)
0
226
(0.0%)
11,594
168
Size 2 - between $300 million and $5 billion in total assets.
Size 3 - $5 billion or more in total assets, excluding the 10 largest
banks.
Size 4 - the 10 largest banks.
Note: The numbers in parenthesis are percentages of the Total
column.
528
26
90
(16.7%)
(4.7%)
(11.5%)
(5.0%)
366
172
1987
Population
(94.5%)
Size 1 - less than $300 million in total assets.
3,055
23
12,121
(16.9%)
557
(13.7%)
10
(94.7%)
1986
Population
47
(88.5%)
(3.2%)
(9.9%)
Total
611
1987
Low capital
Population
Size 4
11,453
(95.8%)
320
(25.8%)
223
Size 3
(87.2%)
Low earnings
C1
(2.6%)
0
(0.0%)
1986
1984
Population
486
391
Population
(23.4%)
0
(0.0%)
0
(0.0%)
Size 2
(17.6%)
1987
Population
(0.4%)
(0.1%)
Size 1
(79.6%)
(23.6%)
2
1985
12,121
460
(0.4%)
41
81
(35.8%)
11,170
226
(18.1%)
Note: The numbers in parenthesis are percentages of the Total
column.
Digitized forFEDERAL
FRASER RESERVE BANK OF ST. LOUIS
21
Table 16
Holding Company Structure of
Risky Banks
Table 17
Charter Types of Risky Banks
1984
1984
Independent
One bank
Multi-bank
Total
4,811
4,567
2,988
12,366
Population
(38.9%)
134
Low capital
(27.6%)
Low earnings
(36.9%)
150
(30.9%)
69
(30.9%)
63
(28.3%)
National
State Member
3,789
830
(30.6%)
(6.7%)
Population
Undercapitalized
(24.2%)
202
Low capital
91
(5.1%)
186
28
(38.3%)
223
Low earnings
(40.8%)
2
(56.4%)
486
(41.6%)
22
(5.8%)
66
12
(29.6%)
1985
Independent
Population
4,215
(34.8%)
Low capital
138
(30.0%)
Low earnings
One bank
4,596
(37.9%)
138
(30.0%)
66
(38.4%)
52
(30.2%)
Multi-bank
3,310
12,121
National
State Member
3,733
832
(30.8%)
(6.9%)
Population
184
460
Undercapitalized
(40.0%)
54
18
(42.9%)
172
5
(11.9%)
189
Low capital
(31.4%)
32
(41.1%)
Low earnings
1986
Independent
One bank
Multi-bank
Total
3,703
4,445
3,456
11,604
(31.9%)
(38.3%)
(29.8%)
Population
Low capital
100
(25.6%)
Low earnings
109
(27.9%)
53
(31.5%)
48
(28.6%)
182
168
Undercapitalized
(39.9%)
19
(11.0%)
National
State Member
3,531
825
(30.4%)
(7.1%)
19
1
(45.2%)
Low capital
1987
Independent
Population
Low capital
One bank
Multi-bank
Total
11,180
3,478
4,450
3,252
(31.1%)
(39.8%)
(29.1%)
101
(30.5%)
Low earnings
90
(39.8%)
93
137
(28.1%)
49
(41.4%)
(21.7%)
(38.5%)
87
(62.6%)
15
39
(38.5%)
272
486
(56.0%)
145
223
(65.0%)
Nonmember
Total
7,556 12,121
(62.3%)
19
42
(45.2%)
239
460
(52.0%)
105
172
(61.0%)
1986
Population
67
(7.0%)
48
(27.9%)
391
(46.5%)
Total
7,747 12,366
1985
Total
(27.3%)
(5.4%)
Nonmember
(2.4%)
146
31
(37.3%)
Low earnings
(7.9%)
53
12
(7.1%)
(31.5%)
331
Nonmember
Total
7,248 11,604
(62.5%)
22
42
(52.4%)
214
391
(54.7%)
103
168
(61.3%)
1987
226
Population
Undercapitalized
National
State Member
3,401
825
(30.4%)
(7.4%)
14
(37.8%)
Independent - banks not owned by a holding company.
One bank - banks owned by a holding company that owns one
bank.
Low capital
Multi-bank - banks owned by a holding company that owns more
than one bank.
Low earnings
104
(31.4%)
57
(25.2%)
2
(5.4%)
24
(7.3%)
17
(7.5%)
Nonmember
Total
6,954 11,180
(62.2%)
37
21
(56.8%)
203
331
(61.3%)
152
226
(67.3%)
Note: The numbers in parenthesis are percentages of the Total
column.
National - national banks.
State member - state banks that are members of the Federal
Reserve System.
Nonmember - state banks that are not members of the Federal
Reserve System.
Note: The numbers in parenthesis are percentages of the Total
column.
JULY/AUGUST 1994
22
this case, managerial incentives better explain
aggressive risk-taking by banks owned by m ulti
bank holding companies. It will require more
extensive study to draw a clear conclusion.
Unfortunately, the scarcity of data on the owner
ship structure of the majority of banks makes the
task difficult.
sistent with the behavior of a subset of banks.
Aggressive risk-taking may not have been a preva
lent phenomenon. The finding that deliberate
risk-taking was confined to a subset of banks,
however, does not rule out the possibility that
increased risk-taking was an important cause of
a large number of bank failures in the 1980s.
The enforcement of regulation may also affect
risk-taking. Table 17 reports the number of risky
banks for each type of charter. A notable pattern
is that the proportions of risky undercapitalized
(Group C l) and low-capital banks (Groups C l and
C2) were relatively high among national banks
throughout the four years examined by this study.
No apparent pattern is found for risky low-earnings banks.
The condition of local economies is found to have
been important for explaining the performance of
banks. This finding implies an important role for
external economic events but does not disprove
the role of deliberate risk-taking. Adverse economic
conditions may have been largely responsible for
the overall deterioration of the financial health of
the banking industry during the 1980s. Yet delib
erate risk-taking may have played a significant
role in many bank failure cases. It appears that
all of the three factors discussed by this article
contributed to the banking problems of the 1980s.
SUM M ARY
There are numerous explanations for the deteri
oration of the asset quality of banks during the
1980s. Moral hazard theories explain the problem
on the basis of increased risk-taking incentives of
bank stockholders, which arise from limited lia
bility and the existence of deposit insurance.
Deregulation in the early 1980s, which increased
both intra- and interindustry competition, increased
stockholders’ incentives to take risk by reducing
the charter values of banks. Another possible
explanation for increased riskiness in banking
is desperate profit-seeking by bank managers to
preserve their jobs. Increased competition and
dwindling profit opportunities sharply lowered
profits of the banks managed by incompetent
managers. To make profits acceptable to stock
holders, incompetent managers needed to increase
risks and hope for a good outcome. W hile these
two explanations blame deliberate risk-taking, it
is also possible that unexpected external events
impaired the financial structure of banks. In
other words, although banks did not change their
behavior, a sequence of adverse economic events
such as the collapse of real estate markets under
mined the financial strength of banks.
This study indicates the presence of ex ante
risk-taking by both bank stockholders and man
agers, but evidence is stronger for moral hazard.
A main finding is that risk measures for banks
with low capital or earnings are distributed heavily
toward both tails. In other words, while many
banks with low capital or earnings refrained from
taking risk, many other banks with similar char
acteristics adopted highly risky strategies. These
findings suggest that moral hazard and desperate
profit seeking by incompetent managers are con
Digitized for FEDERAL
FRASER RESERVE BANK OF ST. LOUIS
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JULY/AUGUST 1994
25
Patricia S. Pollard
Patricia S. Pollard is an economist at the Federal Reserve Bank
o f St. Louis. Richard D. Taylor provided research assistance.
Trade Between the United States
and Eastern Europe
HROUGHOUT MOST OF THE post-World
War II era, trade between the United States and
Eastern Europe was minuscule. The United
States maintained high tariff barriers on imports
from most Eastern European countries and also
restricted its own exports to these countries.
In particular, the United States prohibited the
export to these countries of high-technology
goods related to national security interests.
Eastern Europe also maintained various trade
restrictions on imports from the United States.
Most Eastern European trade was controlled by
the state and conducted within the Council for
Mutual Economic Assistance (CMEA), the trade
organization of the Soviet bloc countries.
With the disintegration of the Soviet system
and the collapse of the CMEA trading bloc,
Eastern European countries began to re-orient
their trade to the West. As these countries
undertook political and economic reforms, the
United States reduced its tariff restrictions on
their products. Consequently, trade between the
United States and Eastern Europe has expanded
substantially since 1988. This paper examines the
growth and pattern of trade between the United
In January 1993, the Czech and Slovak Federal Republic
split into two independent countries: the Czech Republic and
the Slovak Republic. With the exception of total export and
import data, the data used in this paper end before the split
occurred.
States and the three Eastern European countries
which have made the greatest progress in adopt
ing market reforms: the Czech and Slovak
Federal Republic (CSFR), Hungary and Poland.1
Studies have shown that the U.S. economy is
likely to be one of the principal beneficiaries of
economic liberalization in Eastern Europe.2 U.S.
exports to, and investment in, the region should
increase as the restructuring of the economies of
Eastern Europe results in an increase in demand
for capital goods and technology, and opens
new markets for U.S. products. Such gains will
be limited, however, if the Eastern European
countries reverse the pattern of opening their
markets and raise protectionist barriers against
products from the United States.
Despite the initial steps taken to reduce trade
barriers on Eastern European products, the
United States maintains quantitative restrictions
and other forms of protectionism on many prod
ucts from Eastern Europe. Most significantly,
the United States maintains a high degree of
protection against the importation of textiles
and apparel, chemicals, steel and agricultural
products from Eastern Europe. These goods
See, for example, Wang and Winters (1992).
JULY/AUGUST 1994
26
Table 1
Growth in U.S. Trade 1988-931
U.S. imports ($ millions)
U.S. exports (S millions)
1988
1993
Growth
1988
1993
Growth
CSFR2
$87.6
$341.5
289.9%
$55.1
$300.1
444.2%
Hungary
293.9
400.5
36.3
77.5
433.9
459.7
Poland
375.6
454.0
20.2
303.7
916.5
201.8
Combined CSFR,
Hungary, Poland
759.0
1,196.0
57.6
436.3
1,650.5
278.3
441,282.4
580,054.4
31.6
322,718.3
464,767.2
44.0
World
1 Based on nominal dollar values.
2 The 1993 data for the CSFR were calculated by combining the data for the Czech Republic and the Slovak Republic.
SOURCE: U.S. Department of Commerce, Bureau of the Census
are produced by the sectors in which Eastern
Europe is most competitive. The possibility exists
for an increase in protectionism in Eastern Europe
as these countries have become increasingly
frustrated by the lack of progress in securing
access to U.S. as well as other Western markets
for their products. How the problems stemming
from these trade barriers are handled will be an
important determinant of future trade flows
between the United States and the CSFR,
Hungary and Poland.
This paper describes the recent changes in
these trade flows and examines the restrictions
facing Eastern Europe in its trade with the
United States. The structure of the paper is as
follows. Section two provides an overview of
trade between the United States and the CSFR,
Hungary, and Poland. The causes of the recent
growth in trade between the United States and
Eastern Europe are examined in section three.
The product composition of this trade is dis
cussed in section four. Section five examines
U.S. restrictions on the products in which the
CSFR, Hungary and Poland have their greatest
comparative advantage. The conclusions are
presented in section six.
3 The European Union (Belgium, Denmark, France, Germany,
Greece, Ireland, Italy, Luxembourg, the Netherlands,
Portugal, Spain and the United Kingdom) remains the major
trading partner for these three Eastern European countries,
accounting for more than half of their exports and imports.
4 Exports from the United States to the three countries com
bined grew at a faster rate than exports from the European
Union (208 percent compared to 180 percent) between 1988
and 1992 (the latest year for which data for the European
FEDERAL
RESERVE BANK OF ST. LOUIS
OVERVIEW OF TRADE
Trade with the CSFR, Hungary and Poland
has always comprised a low percentage of the
total international trade of the United States.
Neither U.S. exports to these countries nor
imports from any of the three constitute more
than 1 percent of total U.S. exports or imports.
From the perspective of the CSFR, Hungary and
Poland, however, trade with the United States
constitutes a larger share of the international
trade of each country.3
Despite its relatively small size, there has
been a substantial expansion in trade between
the United States and the CSFR, Hungary and
Poland following the disintegration of the Soviet
bloc. In dollar terms, U.S. imports from the three
grew by 58 percent between 1988 and 1993 while
U.S. exports to these three countries grew by
278 percent (see Table 1, and Figures 1 and 2).4
In comparison, total U.S. imports increased by
32 percent between 1988 and 1993 whereas
total U.S. exports rose by 44 percent.
U.S. exports to the CSFR, Hungary and Poland
have grown much faster than imports from these
countries. Consequently, in 1988 the United
Union were available). U.S. imports from the three Eastern
European countries, however, grew more slowly than
European Union imports over the same time period (27 per
cent compared to 133 percent).
27
Figure 1
Total Annual U.S. Imports from Eastern Europe
Millions of dollars
500 450 400 350 300 250 200
-
150 100
-
50 0
-
1988
'
1989
'
1990
'
1991
'
1992
'
1993
SOURCE: U.S. Department of Commerce, Bureau of the Census
Figure 2
Total Annual U.S. Exports to Eastern Europe
Millions of dollars
SOURCE: U.S. Department of Commerce, Bureau of the Census
JULY/AUGUST 1994
28
The Jackson-Vanik Amendment to the Trade
Act of 1974
The Trade Expansion Act of 1951 suspended
the most-favored-nation (MFN) status of any
country deemed to be “under the control of
the world Communist movement.” Between
1951 and 1974, the MFN status of Poland and
Yugoslavia was restored. The U.S. Trade Act
of 1974 reasserted the determination of the
United States to withhold MFN status from
Communist countries. Section 402 of the
Trade Act states that MFN status could not be
granted to any nonmarket economy country
which did not already have such status. The
Act established two exceptions, however,
through which MFN status would be granted:
1) the President reported to Congress that the
country did not restrict the emigration of its
citizens; and 2) the President waived com pli
ance with the freedom of emigration require
ment. The Jackson-Vanik amendment estab
lished the freedom-of-emigration requirement.
This requirement could only be waived if the
President determined that doing so would
“promote the objective of the amendment.”1
MFN status still could not be granted until
the United States had concluded a bilateral
trade agreement with the country in question.
Furthermore, as is standard, the granting of
MFN status was to be done on a reciprocal
basis. Both the waiver of the Jackson-Vanik
amendment and the trade agreement had to
be approved by a congressional resolution.
Waivers were granted for a one-year period,
ending July 3, but could be renewed each
year by the President. Following the renewal
of the waiver, Congress was given 30 days to
pass a resolution eliminating the waiver.
Between 1974 and 1988, no country
was certified to have met the Jackson-Vanik
requirement. Under a waiver of this amend
ment, however, three countries were granted
MFN status: Romania in 1975, Hungary in
1978, and China in 1980. In October 1989,
Hungary was accorded permanent MFN status
following the passage of a freedom-of-emigration law. The Czech and Slovak Federal
Republic was granted waiver status in
November 1990, and permanent MFN status
in October 1991 in accordance with the
Jackson-Vanik amendment. Although such
status was referred to as “permanent,” the
Jackson-Vanik amendment required that the
President report to Congress semiannually on
a country’s compliance with the emigration
criteria. Countries which were not subject
to the Jackson-Vanik requirements (such as
Poland) had unconditional MFN status.
In 1992, President Bush asked Congress to
remove Hungary and the CSFR from the
Jackson-Vanik restrictions, and these
countries were granted unconditional
MFN status.
1 United States International Trade Commission
(June-July 1990, p. 7).
States ran a trade deficit with all three, but by
1993 the deficit had turned to a trade surplus
with Hungary and Poland.
CAUSES OF GROWTH IN U .S .EA STERN EUROPEAN TRADE
The recent growth in U.S. trade with Eastern
Europe is due in part to a general increase in
trade between the former nonmarket economy
countries and the West. The collapse of intraDigitized forFEDERAL
FRASER RESERVE BANK OF ST. LOUIS
CMEA trade due to a movement to market pricing
and the settlement of accounts in convertible
currencies rather than the system of official
exchange rates tied to the Soviet ruble, also
played a part in re-orienting trade to the West.
As these countries sought to modernize their
production processes, they looked to the West
as a source of capital and technology. Exports to
the West provided a source of foreign currency
with which to purchase these capital goods and
were also a source of economic growth following
29
the shrinkage of the domestic market resulting
from the collapse of the old economic system.5
REDUCTION IN U .S. TRADE
B A RRIER S FACING EA STERN
EUROPE
The growth in trade between the United States
and the CSFR, Hungary and Poland also reflects
the reduction of trade barriers by all parties. In
the initial euphoria following the collapse of the
Soviet bloc, the United States pledged to open its
markets to Eastern European products in order to
aid these countries in developing a market system.
One of the first steps the United States took to
encourage reform in Eastern Europe was to grant
most-favored nation (MFN) status to these coun
tries, leading to a substantial reduction in the
tariff rates on imports from Eastern Europe.6
Poland was originally granted MFN status in 1960,
but this status was suspended in January 1981,
following the imposition of martial law. It was
not until November 1989 that Poland regained
its MFN standing. Hungary was granted MFN
status in 1978 under the waiver provision to the
Jackson-Vanik Amendment to the 1974 Trade
Act (see shaded insert on the opposite page for
more on this amendment). The CSFR was the
last of the three countries to gain MFN status, in
November 1990. The importance of MFN status
can be illustrated with reference to the textile and
apparel industry. The MFN tariff rates on U.S.
imports of textile and apparel range from 20 per
cent to 35 percent. In contrast, non-MFN tariff
rates range from 50 percent to over 100 percent.7
Additional changes in the U.S. treatment of
imports from these countries have occurred as
well. In November 1989, Hungary was designated
as a “beneficiary developing country,” making it
eligible for tariff reductions granted under the
5 Although output data for the former nonmarket economies
are not totally reliable, estimates by the International
Monetary Fund (1993) indicate that between 1988 and 1992,
the economy of the CSFR shrank by 23 percent, the
Hungarian economy shrank by 21 percent, and the Polish
economy shrank by 16 percent.
generalized system of preferences (GSP).8 In
January 1990, Poland was deemed eligible for the
GSP and in April 1991 the CSFR was deemed
eligible. As part of the Trade Enhancement
Initiative for Central and Eastern Europe (TEI)
undertaken by the Bush administration in 1991,
the United States expanded the list of products
for which tariff reductions are granted to GSP
countries to include products proposed by the
CSFR, Hungary and Poland. The United States
also concluded bilateral trade agreements with
each country, increasing their import quotas on
textiles and apparel.9
REDUCTIONS IN EASTERN
EUROPEAN TRADE BA R R IER S
FACING THE UNITED STATES
The Eastern European countries also sharply
reduced their barriers to imports. In the CSFR,
most quantitative restrictions on imports were
eliminated or converted into tariffs.10 The average
unweighted tariff rate was 5 percent until January
1992, when the CSFR requested and received
GATT approval to raise its average tariff rate to
6 percent." Hungary has an average unweighted
tariff rate of 13 percent on imports in addition
to a 2 percent customs clearance fee, while the
average tariff on imports in Poland is 13.6 percent.
Both countries have also eliminated most quan
titative restrictions, although Hungary does
maintain quotas on some consumer goods,
while Poland limits imports of some alcoholic
beverages.12 In comparison, the United States
maintains a 6.8 percent average tariff rate on
imports, while the tariff rate for the European
Union and Japan is 6.5 percent.13 All of these
entities also maintain nontariff barriers.
Furthermore, the tariff rates in the CSFR,
Hungary and Poland are lower than most coun
tries at a comparable stage of development.14
8 The Generalized System of Preferences is a program
whereby developed countries grant preferential tariff rates
to products from developing countries. It is allowed under
GATT rules as an exception to the MFN principle. The
United States first granted preferences as part of the Trade
Reform Act of 1974. As noted in the text, not all products
are covered under the GSP.
6 MFN status guarantees that the tariffs imposed on a coun
try’s products will be no higher than those imposed on the
imports of any other country. MFN tariff rates have been
reduced substantially through successive trade rounds held
under the General Agreement on Tariffs and Trade (GATT).
For the period covered in this paper, the average MFN tariff
rate on manufactured goods imported into the United States
was 4 percent. In contrast, non-MFN tariff rates are set by
the Smoot-Hawley Tariff Act of 1930.
13 USITC (August 1991, p. 6).
7 Erzan and Holmes (1992, p. 4).
14 Rodrik (1992, p. 2).
9 Quotas set a limit on the quantity of a product which a coun
try can sell to another country.
10 OECD (1991, p. 84).
11 Green (February 6, 1992).
12 Rodrik (1992, pp. 3-4).
JULY/AUGUST 1994
30
Tariff rates in the CSFR, Hungary and Poland
also tend to be lowest on capital goods and raw
materials, the major U.S. export products to these
countries. In contrast, as discussed below, trade
restrictions in the United States are highest on
the goods for which the three Eastern European
countries have a comparative advantage.
Table 2
Major Product Composition of U.S.
Exports, by End-Use Category
(percent of total)
CSFR
PRODUCT COMPOSITION OF TRADE
More than half of all U.S. merchandise exports
to the CSFR and Hungary, and slightly less than
one-half of U.S. exports to Poland, are capital
goods (Table 2). Although capital goods were
one of the largest categories of U.S. exports to
the CSFR, Hungary and Poland in both 1988 and
1992, there was a clear shift during this period
from industrial supplies and materials to capital
goods. Put simply, there was an increase in the
demand for capital due to industrial restructuring.
Another factor contributing to the shift toward
imports of capital goods is the easing of the
Coordinating Committee on Multilateral Export
Controls (COCOM) restrictions. COCOM was
created in 1949 to control the exportation to the
Soviet bloc countries of products and technology
which could be used for military purposes.15
The importance of the relaxation of COCOM
restrictions is highlighted by the growth in U.S.
exports of computers, semiconductors and
telecommunications equipment—high-technology
industries, relying heavily on research and
development conducted by highly skilled workers.
Such exports grew from 4.9 percent to 20.3 percent
of total exports to the CSFR, from 4.4 percent to
12.4 percent for Hungary, and from 1.0 percent
to 10.9 percent of total U.S. exports to Poland.
In contrast, the CSFR, Hungary and Poland
are countries whose productive resources are
characterized by relatively large amounts of
semiskilled labor, and all suffer from a lack of
up-to-date capital. These factors, in combination
with their relatively low-wage rates, point to
production cost advantages in products requiring
large amounts of semiskilled labor. The product
composition of U.S. imports from the CSFR,
Hungary and Poland does fit this pattern (Table 3).
In 1992, consumer goods, particularly apparel
15 COCOM was disbanded on April 1, 1994. The members of
COCOM were Australia, Belgium, Canada, Denmark,
France, Germany, Greece, Italy, Japan, Luxembourg, the
Netherlands, Norway, Portugal, Spain, Turkey, the United
Kingdom and the United States.
Digitized forFEDERAL
FRASER RESERVE BANK OF ST. LOUIS
Hungary
Poland
1988 1992 1988 1992 1988 1992
Food & beverages
0.8
3.9
0.7
2.1
38.1
15.4
Industrial supplies
44.2
4.3
37.8
8.9
24.3
7.9
Capital goods
46.2
73.8
40.3
61.5
15.2
45.8
2.7
11.4
7.0
1.3
2.7
Automotive
0
Consumer goods
5.8
12.0
7.9
17.0
7.8
13.0
Exports, n.e.c.
3.1
3.3
1.9
3.4
13.4
15.2
and footwear, accounted for the largest category
of U.S. imports from each country.
The CSFR and Poland have increased their
exports of capital goods to the United States,
although these goods are not high-technology
products. For the CSFR and Poland, nearly all
capital goods exported to the United States are
nonelectrical machinery and parts. Within this
group, industrial and agricultural machinery,
and machine tools are the most important.
A more formal way to analyze the exports of a
country is to calculate an index of relative com
parative advantage (RCA). This index is calcu
lated as follows:
where X n are exports of commodity n; i is the
country of origin; j is the country of destination;
and - j is the rest of the world (all countries
excluding country j ) . Equation 1 indicates that
the relative comparative advantage of country i in
any good n depends on the share of that good in
country i ’s exports to country j relative to the
share of good n in the rest of the world’s exports
to country;. In general, if this ratio is greater
than 1, then country i has a comparative advan
tage in producing that product relative to the
rest of the world.16
16 For more details on this index and its use in determining the
comparative advantages of Eastern European countries, see
Murrell (1990) and USITC (1991).
31
categories each of the three Eastern European
countries has the greatest relative comparative
advantage, and also to look at changes in each
country’s comparative advantage as each has ini
tiated the transition to a market economy.18
Table 3
Major Product Composition
of U.S. Imports (percent of total)
CSFR
Hungary
1988 1992 1988 1992
Poland
1988 1992
Food & beverages
5.6
4.1
20.5
17.0
35.9
15.0
Industrial supplies
21.6
23.2
20.4
17.2
26.9
29.3
Capital goods
16.6
22.2
6.3
13.5
10.5
18.3
Automotive
Consumer goods
Exports, n.e.c.
5.0
3.8
13.9
14.5
0.8
1.4
49.3
43.1
38.2
36.8
24.7
33.9
2.0
3.6
0.8
1.0
1.2
2.2
Table 4 shows the relative comparative advantage
indexes for each of the three Eastern European
countries, by principal end-use category of exports
in 1988 and 1992, based on U.S. Bureau of the
Census data. Appendix tables provide the RCAs
for each country using five-digit, end-use cate
gories in each year from 1988 to 1992.
CHANGES IN RELATIVE
COMPARATIVE ADVANTAGE
Two major developments occurred between
1988 and 1992 that may have affected the rela
tive comparative advantages of the Eastern
European countries. The first was the progress
made in moving from a command system of pro
duction to a market-oriented one. Producer and
consumer prices were decontrolled, government
subsidies to industry were reduced or in many
cases eliminated, and privatization programs
were implemented. These measures should
eventually result in more efficient production
leading to an index of comparative advantage
more directly related to market forces.
For example, in 1992 the CSFR exported $242
million of merchandise to the United States,
with shipments of footwear accounting for $14
m illion of this total. In contrast, world merchan
dise exports to the United States totalled $532
billion in 1992, and footwear exports accounted
for $7 billion of this total. Thus, whereas footwear
comprised nearly 6 percent of the merchandise
exports of the Czech and Slovak Federal Republic
to the United States, it accounted for slightly
more than 1 percent of world exports to the
United States. Since the share of footwear in
the CSFR’s exports to the United States was
larger than the share of footwear in world exports
to the United States, the CSFR is said to have a
relative comparative advantage in this product
(RCAfootwear> l) .17 If the share of footwear in the
CSFR’s exports to the United States had been
smaller than the share of footwear in world
exports to the United States, the CSFR would
have a relative comparative disadvantage in this
product (RCAfoo,wear< l).
The second development was the easing of
trade restrictions by the United States. As noted
above, only Hungary enjoyed MFN status in its
trade with the United States in 1988, and none
of the three countries was considered eligible for
GSP status.19 By 1992, all three had both MFN
and GSP status, as well as increased quotas for
textiles and apparel. The relaxation of these
restrictions should allow the computed relative
comparative advantage to more accurately reflect
the true comparative advantage of each country.
Using the index of relative comparative advan
tage, it is possible to determine in which product
Despite these two developments, the evidence
presented in Table 4 and the Appendix does not
17 More precisely, the index of relative comparative advantage
for footwear from the CSFR is
14,270,978
7,294,287,012
------------------:----------------------------= .05895
242,077,791 532,017,422,033
„
.01371 = 4.3
18 Another standard method used is revealed comparative
advantage, which is calculated by
x; -/w;
x; +m; ’
(1990) and Collins and Rodrik (1991) to calculate the com
parative advantages of the Eastern European countries in
trade with the West prior to economic liberalization. Both of
these studies calculate the index of comparative advantage
only for major product categories, but their results are similar
to the results based on 1988 data used in this paper.
19 The United States did not extend GSP benefits to the Soviet
bloc countries.
the difference between country i ’s exports of good n and its
imports of good n divided by the sum of country i ’s exports
and imports of good n. This index was used by Fieleke
JULY/AUGUST 1994
32
Table 4
Relative Comparative Advantage Indexes: By Principal End-Use Category
CSFR
Hungary
Poland
Category
1988
1992
1988
1992
1988
1992
0
1.00
0.78
3.64
3.26
6.41
2.87
Agricultural
00
1.41
1.07
5.14
4.51
8.44
3.49
Nonagricultural
01
0.05
0.05
0.18
0.10
1.70
1.28
1
0.81
0.89
0.76
0.66
1.01
1.13
Energy products
10
0.00
0.00
0.02
0.02
0.00
0.04
Paper & paper products
11
0.04
0.01
0.01
0.00
0.00
0.00
4.82
Foods, feeds & beverages
Industrial supplies & materials
12000 & 121
4.81
7.45
5.48
1.55
3.74
Chemicals, excluding medicinals
125
0.40
1.27
0.97
1.16
0.63
1.31
Building materials, except metals
13
0.52
0.20
0.02
0.00
0.08
0.39
Metals
14
2.19
0.73
0.64
0.39
1.89
0.75
Textile supplies & related materials
Metallic products
15
0.81
0.80
2.50
4.07
2.54
4.75
Nonmetallic minerals & nonmetallic prods.
16
0.73
0.48
0.53
1.07
0.23
0.14
2
0.72
0.88
0.27
0.54
0.46
0.72
Capital goods except automotive
Electric generating machinery, electric
20
0.31
0.07
0.31
1.29
0.12
0.79
Nonelectric incl. parts & attachments
21
0.93
1.11
0.30
0.50
0.48
0.74
Transportation equipment, except auto.
22
0.00
0.06
0.01
0.05
0.68
0.51
Automotive vehicles, parts & engines
3
0.25
0.22
0.70
0.84
0.04
0.08
Consumer goods (nonfood), except auto.
4
2.25
1.87
1.75
1.59
1.13
1.46
Consumer nondurables, manufactured
40
2.68
1.84
2.72
2.29
1.49
1.62
Consumer durables, manufactured
41
1.59
1.44
1.08
1.06
0.92
1.45
Unmanufactured consumer goods
42
4.68
6.17
0.01
0.02
0.12
0.08
50
0.68
1.09
0.26
0.31
0.43
0.65
apparatus & parts
Exports not elsewhere counted
show major shifts in relative comparative advan
tage between 1988 and 1992. In general, the
product categories in which a country exhibited
a relative comparative advantage (RCA>1) in 1988
are the same as those in 1992, and vice versa.20
Furthermore, Hungary, which had made the most
progress toward reforming its economy at the
start of 1988 and faced the lowest tariffs on its
exports to the United States of the three countries,
had no fewer shifts in its relative comparative
advantage (movements from RCA>1 to RCA<1,
and vice versa) between 1988 and 1992 than the
CSFR or Poland.
The lack of major shifts in relative comparative
advantage is not surprising given the years needed
to restructure the production of the formerly
command-based economies. Such restructuring
could change the pattern of comparative advan
tage of the Eastern European countries. There is
some evidence, however, that the estimates given
in this paper may be close to reflecting the com
parative advantage of each country which will
prevail after the transition to a market-based
system is completed within the CSFR, Hungary
and Poland. The product composition of each
country’s trade with the West was different from
20 Another method to determine changes in relative compara
tive advantage is to compute a rank correlation coefficient
for each country. A rank correlation coefficient of 1 indicates
no change in the ordering of industries by the RCA index
between 1988 and 1992, zero indicates no relationship
between the 1988 ordering and the 1992 ordering, and
-1 indicates a complete reversal in the ordering. The rank
correlation coefficients are .74 for the CSFR, .77 for Hungary,
and .63 for Poland, using the five-digit product categories.
Digitized forFEDERAL
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33
its trade with the other CMEA members. As
noted by Collins and Rodrik (1991), Eastern
Europe’s trade with the West was less distorted
than its intra-CMEA trade and, thus, more likely
to be reflective of its comparative advantage.21
With respect to intra-CMEA trade, the products
traded and their prices were set through bilateral
government agreements.22 In contrast, products
exported to Western countries and the prices of
these products were subject to international
competition. An OECD study of Hungary found
that even prior to 1989, Hungary based its trade
with the West on its comparative advantage.23
There is little evidence that the CSFR, Hungary
or Poland have redirected their intra-CMEA
sales to the West.24
Relative Comparative
Advantage in 1992
The one-digit, end-use categories show that the
CSFR, Hungary and Poland exhibited a relative
comparative advantage in consumer goods in
1992. The latter two countries also had a com
parative advantage in foods, feeds and beverages.
On a more disaggregated basis, all three coun
tries in 1992 exhibited a relative comparative
advantage in agricultural goods, textile supplies
& related materials, chemicals (excluding medicinals), and manufactured consumer goods.
Among consumer goods, all three countries had
a relative comparative advantage in some type
of textile apparel & household goods made from
textiles, and footwear.25 In addition, Hungary
and Poland had a relative comparative advantage
in m etallic products.
In summary, these three Eastern European
countries exhibit a relative comparative advantage
in agricultural products, chemicals, textiles,
apparel and footwear, with the exception of the
CSFR in metallic products.26 This pattern of
comparative advantage fits the typical pattern
for developing countries.27
21 Collins and Rodrik (1991, p. 50).
22 OECD (1992, p. 83).
23 OECD (1993, p. 91).
24 See, for example, Rodrik (1992, p. 18) and OECD (1993,
pp. 91-3).
25 See the Appendix for details.
26 These findings are supported by changes in prices relative
to the overall producer price indexes in Hungary and Poland
between 1989 and 1991. In conjunction with the liberaliza
tion of prices, reductions in subsidies, and the progress
made in making their currencies convertible, Hungary and
Poland both experienced a decline in the prices of textiles,
If these sectors do indeed represent the compar
ative advantage of the CSFR, Hungary and Poland,
one would expect to see further increases in the
export to the United States of these products.
Furthermore, as these countries become more
adept at marketing and supplying goods for
export, trade in these products should increase.
In actuality, however, the potential for increased
exports to the United States of the products in
which the three have a comparative advantage
is limited by the fact that these goods fall into
the “sensitive sectors” categorization. These
are products typically produced by sectors in
decline and are highly protected from interna
tional competition.
U .S. TRADE RESTRICTIONS ON
EA STERN EURO PEAN PRODUCTS
The initial emphasis in the United States on
opening its markets to Eastern European products
has given way to protectionist sentiments as the
CSFR, Hungary and Poland have shown that they
can compete successfully with certain Western
industries and, as a consequence, imports to the
United States from these countries have expanded.
As noted above, many sectors in which Eastern
Europe is most competitive are highly protected
in the United States. For example, the textile,
apparel and footwear industries enjoy the highest
level of tariff protection of all U.S. manufacturing
industries. Tariff rates for textiles and apparel
average 18 percent ad valorem, while tariffs
on certain footwear products range as high as
40 percent.28 The U.S. dairy industry also enjoys
a high level of tariff protection, with rates ranging
from 10 percent to 25 percent.29 Furthermore,
none of these products are eligible for GSP tariff
reductions.
In addition to the tariff barriers facing Eastern
Europe on the products in which it has a com
parative advantage, most of these products are
subject to nontariff barriers. For example, the
clothing, leather and metal products relative to their producer
price indexes. Hungary also saw a drop in the relative price
of food, while Poland experienced a fall in the relative price
of chemicals. The decline in the relative prices of these
products was due primarily to the availability of lower cost
inputs and an increase in production efficiency. See the
Organization for Economic Co-operation and Development
(1993) for the details of the relative price changes.
27 Bank for International Settlements (1993, p.70) and Collins
(1991, p. 223).
28 For a further discussion of U.S. tariff protection, see Finger
(1992) and Ray (1991).
29 U.S. Harmonized Tariff Schedule 1993.
JULY/AUGUST 1994
34
United States maintains quotas on textiles,
apparel and some agricultural products, most
notably dairy products, a category in which the
CSFR, Hungary and Poland have a relative com
parative advantage. In addition, quotas on steel
exports to the United States from these countries,
as well as from many others, were in place during
most of the period covered in this paper.
Although many of the quotas which apply to the
CSFR, Hungary and Poland remain underutilized,
they still may act as an effective restraint on trade.
Quotas are not applied by major product category
but to specific products. Thus, rather than setting
a limit on the importation of wool clothing, the
United States places limits on specific types of
wool clothing— for example, m en’s and boy’s
wool suit-coats. The quota limit on a specific
product may be so low that it is not profitable to
export such a small quantity. Furthermore, the
quota agreement may require that exports be
spread out over each year, further limiting the
profitability of trade. For example, the agreement
limiting the export of Polish steel to the United
States prohibited Poland from exporting more
than 60 percent of its yearly quota allotment in
any two consecutive quarters.30 The 1992 textile
agreement between the United States and the
CSFR requires the latter to space its exports to
the United States “within each category evenly
throughout each agreement period.”31
The United States has restricted the flow of
certain goods simply by threatening to place limits
on their importation. For example, the most
recent textile agreement between the United
States and Poland lists products for which no
quotas are set, but for which the United States
reserves the right to “consult” with the govern
ment of Poland to restrain the trade of these
products if the United States believes such
products are causing “market disruption” or the
“risk of market disruption.” The agreement even
sets limits on imports of these products while
consultations are in progress.32 Another method
30 USITC (March 1990, p. 11-8).
31 United States Department of State (July 21, 1992, p. 4).
32 See U.S. Department of State (January 28, 1992, pp. 8-10).
33 Dumping is the practice of selling a product in foreign mar
kets at a lower price than in the home market, or at price
below the cost of production. For an analysis of the use of
anti-dumping regulations as a protectionist device, see
Coughlin (1991).
34 The United States is not alone in restricting access to prod
ucts from Eastern Europe. The European Union, despite
concluding association agreements with the CSFR, Hungary
RESERVE BANK OF ST. LOUIS
FEDERAL
used to restrict exports of sensitive products to
the United States is anti-dumping regulations.33
Tariff barriers, nontariff barriers and anti-dumping
measures have all been used to restrict the flow
of goods from the CSFR, Hungary and Poland to
the United States. Although some relief has been
granted to Eastern Europe in recent years, restric
tions still prevail on the products in which these
countries have a relative comparative advantage.34
The importance of these restrictions for each sector
are discussed below.
Steel
The granting of MFN status to the CSFR and
Poland reduced the tariffs they faced on steel
exports to the United States from an average of
20-25 percent to an average of less than 5 percent.35
However, quota restrictions and anti-dumping
measures act as limits on steel products. Until
March 1992, steel from the CSFR, Hungary and
Poland was subject to quantitative restrictions.
These limits were raised in 1989 and 1991, and,
as part of the Trade Enhancement Initiative for
Central and Eastern Europe, the United States
committed itself to adjusting the ceilings further,
either through increased flexibility in the admin
istration of the quotas, or increasing the actual
quotas.36 This commitment, however, was never
acted upon. At the end of March 1992, the
United States allowed all of the quantitative
restrictions on steel to elapse.
The end of quantitative restrictions on U.S.
steel imports did not open the U.S. market to
steel products from Eastern Europe. Within two
months of the elimination of quotas, the U.S.
steel industry accused every significant foreign
supplier of steel to the United States of dumping
their product in the U.S. market. In the summer
of 1993, the USITC ruled that steel producers in
19 countries had dumped their products in the
U.S. market, and that this action had resulted in
injury or the potential for injury to the U.S. steel
industry. In accordance with this finding, the
and Poland, still maintains restrictions on many products,
most notably, agricultural, chemicals, iron and steel, textiles
and apparel, and footwear.
35 See USITC (November 1991, p. 117).
36 As noted in the text, not only did the United States place lim
its on each type of steel product but even in the amount
which could be imported during subperiods of the year.
35
USITC imposed duties ranging from 18 percent
to 109 percent of the value of the steel product
on imports from the dumping countries. Dumping
duties on Polish exports to the United States of
carbon steel plate were levied at 62 percent,
effectively eliminating Polish exports of this
product to the U.S. market. Although no charges
of dumping were filed against the CSFR and
Hungary, the size and extent of the dumping
duties is likely to limit the growth of steel
exports to the United States from all countries.37
Prior to the anti-dumping case, the CSFR,
Hungary and Poland had begun programs to make
their “steel enterprises more market-oriented, costconscious and perhaps more export oriented.”38
Use of anti-dumping measures by the United
States is an indication to these countries that
even if they follow the prescriptions of the West
and develop an efficient industry, they still may
be denied access to U.S. markets.
Textiles and A pparel
U.S. imports of textiles and apparel from the
CSFR, Hungary and Poland are covered by quotas
in accordance with the Multifiber Arrangement.39
Before the granting of MFN status to the CSFR
and Poland, quota utilization rates (which indi
cate how close a country comes to meeting the
quota on a particular product) for these countries
were very low, because the tariffs acted as an
effective barrier to trade.40 Even though MFN
tariffs are high, utilization rates have increased
since the granting of MFN status. Utilization
rates rose even as the United States has negotiated
new textile and apparel agreements with the
CSFR, Hungary and Poland which have increased
these quotas.
Under the Trade Enhancement Initiative for
Central and Eastern Europe, the United States
pledged to take steps to increase its imports of
textiles and apparel from Eastern Europe. In
accordance with this initiative, the United
States raised the quotas on some imports from
the CSFR, Hungary and Poland. The United
States also promised to consider setting quotas
for more broadly defined product categories
which would allow the countries more flexibility
in meeting the quotas.41
Chemicals
Tariffs on industrial chemicals and fertilizers
average only 2 percent ad valorem and, thus,
since the granting of MFN privileges to all three
countries, they do not represent a significant
barrier to trade. According to the Organization
for Economic Co-operation and Development
(OECD), the main obstacle to the growth of
Eastern European chem ical exports has been
the use of anti-dumping measures by the West.42
For example, the U.S. chem ical industry filed
dumping charges in 1992 against the imports
of sulfanilic acid from Hungary.43 The USITC
found preliminary evidence that the Hungarian
producers were dumping this product in the
United States and causing harm to the U.S.
chem ical industry. Temporary duties equal to
58 percent of the value of Hungarian shipments
of sulfanilic acid were assessed. These duties
were rescinded when, in its final decision in
February 1993, the USITC ruled that there was
not sufficient evidence that these imports were
injuring the domestic industry.
Agriculture
Agricultural exports from the CSFR, Hungary
and Poland are affected both by U.S. agricultural
subsidies and nontariff barriers. According to the
USITC, the only nontariff barriers in agriculture
that significantly affect the CSFR, Hungary and
37 The imposition of duties which block certain producers from
the U.S. market does not necessarily lead to an increase in
imports from the “nondumping” producers. The U.S. indus
try is free to file charges of dumping against foreign competi
tors at any time. Thus, the finding of dumping may act as a
deterrent to other producers to expand their exports to the
United States.
40 As noted in the text above, non-MFN tariffs in textiles range
from 50 percent to 100 percent, while MFN tariffs range from
20
percent to 35 percent.
38 USITC (November 1991, p. 117).
41 See USITC (November 1991, p. 46).
39 The Multifiber Arrangement (MFA) refers to the bilaterally
negotiated quota restrictions on textiles and apparel, which
are placed by developed countries on imports from develop
ing countries. The MFA is negotiated under the auspices of
the GATT committee on textiles. See Hamilton (1990).
If Congress approves the GATT Uruguay Round of mulitilateral trade agreements, the MFA will be phased out over a
42 OECD (1992, p. 92).
10-year period beginning in July 1995. Quota restrictions
on textiles and apparel are then to be replaced by GATTnegotiated tariffs.
43 Sulfanilic acid is a gray-white to white crystalline solid. Its
main uses are in the production of synthetic dyes that in turn
are used in foods, drugs and cosmetics, and in the produc
tion of optical brightening agents. Sulfanilic acid is also
used in concrete additives. (USITC, February 1993.)
JULY/AUGUST 1994
36
Poland axe the quantitative restrictions on cheese
imports.44 Most cheese products are covered by
quotas and those which are not face high tariff
barriers. Furthermore, as noted above, cheese
products are not eligible for GSP treatment.
As part of the TEI, the United States committed
itself to increasing the access of cheese products
from these countries into the U.S. market. None
theless, no progress has been made on this pro
posal. For example, in 1991 Hungary petitioned
the United States to allow GSP benefits for the
importation of goya cheese, one of the few cheeses
for which importation into the United States is
not limited by quotas. Imports, however, are
restricted by a 25 percent tariff. Hungary provided
25 percent of the total U.S. imports of goya cheese
in 1990. Although no goya cheese is produced
in the United States, the U.S. dairy industry
opposed the extension of GSP benefits to goya
cheese, arguing that this product was a substitute
for domestically produced, hard, Italian-type
cheeses.45 Because of this opposition, the United
States refused Hungary’s request to add goya
cheese to the list of GSP-eligible products.
CONCLUSION
Foreign trade is vitally important for the CSFR,
Hungary and Poland to facilitate the re-structuring
of their economies. These countries are depen
dent upon exports to ensure a supply of foreign
currency to finance capital purchases (reducing
the pressures to incur foreign debt), and to pro
mote economic growth, which in turn is critical
to their political stability.
The governments of the CSFR, Hungary and
Poland have made great progress over the past few
years in reforming their economies. The role of
the state has been reduced substantially through
the deregulation of prices, the privatization of
industries, and the adoption of legislation aimed
at fostering the market system. Furthermore, all
of these countries have substantially liberalized
their trading environments by eliminating quotas,
harmonizing tariffs, and permitting the convert
ibility of their currencies. Officials in these coun
tries cite the continuation of Western trade barriers
as one of the primary hindrances to their successful
transition to market democracies.46
44 USITC (April 1992, p. 18).
45 See USITC (March 1992) for details.
46 Burke (January 19, 1994).
Digitized forFEDERAL
FRASER RESERVE BANK OF ST. LOUIS
The United States’ economic growth has benefitted from the reforms undertaken by the Eastern
European countries. Most notably, U.S. exports
to these countries have expanded substantially.
Despite these gains, the United States continues
to restrict access to its markets to goods produced
in Eastern Europe. As shown in this article, the
products in which the CSFR, Hungary and Poland
have the greatest comparative advantage are pre
cisely those in which the United States maintains
the greatest restrictions on trade. Reducing the
trade barriers to these products will spur economic
growth in Eastern Europe, and is an important
step the West can take to ensure that the coun
tries of Eastern Europe continue along the path
of reform.
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Bank for International Settlements. 63rd Annual Report,
June 1993.
Burke, Justin. “Central European Countries Cite Obstacles to
Economic Integration,” The Christian Science Monitor,
January 19, 1994, p. 9.
Collins, Susan M., and Dani Rodrik. Eastern Europe and the
Soviet Union in the World Economy. Institute for
International Economics, May 1991.
Collins, Susan M. “Policy Watch: U.S. Economic Policy
Toward the Soviet Union and Eastern Europe,” The Journal
o f Economic Perspectives (fall 1991), pp. 219-27.
Coughlin, Cletus C. “U.S. Trade-Remedy Laws: Do They
Facilitate or Hinder Free Trade?” this Review (July/August
1991), pp. 3-18.
Erzan, Refik, and Christopher Holmes. “The Restrictiveness of
the Multi-Fibre Arrangement on Eastern European Trade,"
Policy Research Working Papers, WPS 860, The World
Bank (February 1992).
Fieleke, Norman S. “Commerce With the Newly Liberalizing
Countries: Promised Land, Quicksand, or What?” New
England Economic Review (May/June 1990), pp. 19-33.
Finger, Michael J. ‘Trade Policies in the United States,”
National Trade Policies, Handbook o f Comparative
Economic Policies, vol. 2. Greenwood Press, 1992,
pp. 79-108.
Green, Paula L. “U.S. Monitors EC Ties With Eastern Europe,”
Journal of Commerce (February 6, 1992).
Hamilton, Carl B., editor. Textiles Trade and the Developing
Countries: Eliminating the Multi-Fibre Arrangement in the
1990s. The World Bank, 1990.
International Monetary Fund. World Economic Outlook
(May 1993).
Murrell, Peter. The Nature of Socialist Economies: Lessons
from Eastern European Foreign Trade. Princeton University
Press (1990).
37
Organization for Economic Co-operation and Development.
Economic Surveys: Czech and Slovak Federal Republic.
OECD, December 1991.
_____ . Reforming the Economies of Central and Eastern
Europe. OECD, 1992.
_____ . Economic Surveys: Hungary. OECD, 1993.
Ray, Edward J. “Protection of Manufacturers in the United
States,” in David Greenaway and others, eds., Global
Protectionism. St. Martin’s Press, 1991, pp. 12-39.
Rodrik, Dani. “Foreign Trade in Eastern Europe’s Transition:
Early Results,” National Bureau of Economic Research
Working Paper Series No. 4064 (May 1992).
U.S. Department of State, Bureau of Economic and Business
Affairs, Textiles Division. “United States and the Republic of
Poland Sign New Textile Agreement” (Textiles Division,
Public Release, January 28, 1992).
_____ . “United States and the Czech and Slovak Federal
Republic Amend Their Bilateral Textile Agreement” (Textiles
Division, Public Release, July 21, 1992).
United States International Trade Commission. U.S. Laws and
U.S. and EC Trade Agreements Relating to Nonmarket
Economies. USITC, March 1990.
United States International Trade Commission, Office of
Economics. “Legislation to Ensure Role for Congress in
Extending MFN Status to Nonmarket Economy Countries,”
International Economic Review (June-July 1990),
pp. 7-8.
_____ . “Liberalization of Foreign Trade in Czechoslovakia,
Hungary, and Poland: Progress and Prospects,”
International Economic Review (August 1991), pp. 5-7.
United States International Trade Commission. Central and
Eastern Europe: Export Competitiveness of Major
Manufacturing and Services Sectors. USITC Publication
2446 (November 1991).
_____ . President’s List of Articles Which May Be Designated
Or Modified As Eligible Articles For Purposes of the U.S.
Generalized System of Preferences. USITC Publication
2491 (March 1992).
_____ . Trade Between the United States and China, the
Former Soviet Union, Central and Eastern Europe, the Baltic
Nations, and Other Selected Countries During 1991. USITC
Publication 2503 (April 1992).
_____ . Sulfanilic Acid from the Republic of Hungary and India.
USITC Publication 2603 (February 1993).
Wang, Z.K., and L. Alan Winters. ‘The Trading Potential of
Eastern Europe,” Journal of Economic Integration (autumn
1992), pp. 113-36.
JULY/AUGUST 1994
38
Appendix
Index of Relative Comparative Advantage: CSFR
1991
1992
3.597
1.072
0.031
3.616
4.585
4.418
0.047
3.189
1.130
0.000
0.000
0.017
0.495
0.151
0.231
0.731
0.270
0.000
1.184
0.000
0.000
3.019
0.028
0.000
0.000
0.116
00190— Wine & related products
3.415
3.773
4.261
4.305
1.546
00200— Feedstuff and foodgrains
0.129
7.632
16.709
12.935
11.816
01000— Fish & shellfish
0.049
0.000
0.000
0.000
0.000
01010— Alcoholic beverages, except wine
0.010
0.944
0.077
0.038
0.126
01020— Other nonagricultural foods & food additives
0.133
0.595
0.885
0.468
0.530
10010— Fuel oil
0.000
0.004
0.000
0.000
0.000
10020— Other petroleum products
0.002
0.004
0.000
0.000
0.001
10030— Liquified petroleum gases
0.000
0.000
0.000
0.000
0.000
10100— Coal & other fuels, except gas
0.000
0.000
0.000
0.032
0.000
10300— Nuclear fuel materials & fuels
0.000
0.000
0.000
0.005
0.000
11000— Pulpwood and woodpulp
0.000
0.080
0.000
0.000
0.000
11100— Newsprint
0.038
2.309
0.000
0.000
0.000
11110— Paper & paper products, n.e.s.
0.080
0.000
0.000
0.017
0.041
12000— Cotton, wool & other natural fibers
0.000
3.923
0.000
0.000
0.000
12030— Hides & skins, & fur skins-raw
0.417
0.000
0.000
0.000
0.000
12060— Farming materials, including farm animals
0.000
0.031
0.125
0.410
0.366
12070— Other (tobacco, waxes, nonfood oils)
0.004
6.477
14.058
8.566
8.418
12100— Cotton cloth & fabrics, thread & cordage
3.268
4.971
2.902
1.812
3.902
12110— Wool, silk & other vegetable fabric
7.372
14.032
17.173
19.819
23.339
12135— Synthetic cloth & fabric, thread
0.528
5.618
5.218
9.048
10.218
12140— Other materials (hair, synthetics, etc.)
67.477
12.076
0.000
0.200
0.000
12150— Finished textile industrial supplies
11.145
3.257
1.468
1.555
0.776
0.000
0.012
0.341
0.000
0.932
12320— Other materials, except chemicals
1.637
0.070
0.040
0.068
0.000
12500— Plastic materials
0.100
0.278
0.276
0.091
0.090
12510— Fertilizers, pesticides, and insecticides
0.007
0.000
0.023
0.000
0.000
12530— Industrial inorganic chemicals
0.863
3.117
0.736
1.282
2.610
12540— Industrial organic chemicals
0.732
0.075
0.114
0.439
0.500
12550— Other chemicals (coloring agents, print inks, paint)
0.026
0.418
0.100
1.726
4.199
13000— Lumber & wood in the rough
0.074
0.428
0.040
0.000
0.005
13010— Plywood & veneers
0.000
0.000
0.015
0.000
0.000
0.225
Product
1988
1989
1990
00100— Meat, poultry & other edible animals
3.692
3.938
00110— Dairy products & eggs
3.215
3.239
00120— Fruits & preparations
0.046
0.013
00130— Vegetables & preparations
0.034
00160— Bakery & confectionery products
0.360
00170— Tea, spices & preparations
0.000
00180— Other (soft beverages, processed coffee, etc.)
12160— Leather & furs-unmanufactured
13020— Stone, sand, cement & lime
0.000
0.859
0.266
0.077
13100— Glass-plate, sheet, etc. (excluding automotive)
5.740
5.540
6.474
2.646
8.581
13110— Other-finished (shingles, molding, etc.)
1.676
0.280
0.302
0.140
0.089
13120— Nontextile floor & wall tiles and other covering
0.000
0.338
0.045
0.000
0.052
14000— Steelmaking & ferroalloying material
0.000
0.000
0.000
1.882
1.462
14100— Iron & steel mill products-semifinished
6.779
5.233
1.603
1.936
1.828
14200— Bauxite & aluminum
0.000
0.000
0.000
0.000
0.000
Digitized for FEDERAL
FRASER RESERVE BANK OF ST. LOUIS
39
Product
1988
1989
1990
1991
1992
14220— Copper
0.000
0.000
0.000
0.000
0.013
14240— Nickel
0.736
0.000
0.000
0.000
0.010
14280— Other precious metals
0.000
0.000
0.000
0.000
0.000
14290— Miscellaneous nonferrous
0.050
0.000
0.000
0.550
0.346
15000— Iron and steel products, except advanced
1.911
2.256
0.664
3.417
1.730
15100— Iron and steel manufactured, advanced
0.044
0.008
0.014
0.285
0.834
15200— Finished metal shapes, except steel
0.006
0.004
0.042
0.042
0.098
16040— Sulfur & nonmetallic minerals
5.051
0.037
0.000
0.000
0.016
16050— Other (synthetic rubber, wood, cork, gums, etc.)
0.000
0.000
0.000
0.000
0.120
16120— Other (boxes, belting, glass, abrasives, etc.)
0.370
0.160
0.355
0.484
0.735
0.103
20000— Generators, transformers & accessories
0.977
0.019
0.000
0.074
20005— Electric apparatus & parts, n.e.c
0.008
0.049
0.002
0.065
0.061
21000— Drilling & oil field equipment
10.966
10.488
5.828
5.448
0.000
21010— Specialized mining & oil processing equipment
0.000
0.000
0.000
0.434
1.833
21030— Excavating, paving & construction
0.040
0.016
0.000
0.350
0.863
21040— Nonfarm tractors & parts
1.440
4.487
3.207
0.434
0.797
21100— Industrial engines, pumps, compressors & generators
0.000
0.002
0.081
0.115
0.093
21110— Food & tobacco processing machinery
0.000
0.000
0.000
0.118
0.483
21120— Machine tools, metal working
3.611
2.725
3.775
2.599
4.361
21130— Industrial textiles, sewing, & leather working machinery
2.023
3.872
3.845
6.689
6.092
21140— Woodworking, glass working, and plastic machinery
0.014
0.004
1.492
1.125
0.308
21150— Pulp & paper machinery
2.249
3.725
5.315
1.998
2.347
0.363
0.838
21160— Measuring, testing & control instruments
0.000
0.036
0.343
0.197
21170— Materials handling equipment
0.000
0.006
0.437
1.331
21180— Other industrial machinery
0.158
0.454
1.461
4.629
5.436
21190— Photo & other service industry machinery
0.076
0.138
0.019
0.221
0.179
13.782
14.761
22.738
11.487
9.580
21200— Agricultural machinery and equipment
21300— Computers
0.000
0.000
0.000
0.004
0.006
21301— Computer accessories, peripherals
0.001
0.105
0.025
0.003
0.062
21320— Semiconductors
0.000
0.000
0.000
0.014
0.009
21400—Telecommunications equipment
0.033
0.777
0.318
0.698
0.697
21500— Business machinery & equipment, except computers
0.283
0.121
0.183
0.070
0.050
21600— Laboratory, testing & control instruments
0.000
0.000
0.165
0.079
0.335
21610— Other scientific, medical & hospital equipment
0.000
0.000
0.045
0.016
0.085
22000— Civilian aircraft, complete - all
0.000
0.000
0.127
0.023
0.086
22010— Parts for civilian aircraft
0.002
0.006
0.000
0.070
0.161
22020— Engines for civilian aircraft
0.000
0.000
0.000
0.037
0.007
22220— Marine engines & parts
0.000
0.000
0.000
0.000
0.000
30000— Complete & assembled-new & used
0.001
0.000
0.000
0.000
0.000
30100— Complete & assembled
0.004
0.478
0.000
0.000
0.016
30200— Engines & engine parts
0.000
0.008
0.020
0.085
0.114
30220— Automotive tires & tubes
10.637
9.019
12.498
13.744
9.249
30230— Other parts & accessories
0.000
0.023
0.005
0.011
0.049
40000— Apparel & household goods-cotton
0.689
0.398
0.398
0.709
1.023
10.616
40010— Apparel & household goods-wool
20.882
13.846
14.072
20.096
40020— Apparel & household goods-other textiles
0.042
0.542
0.436
0.894
0.974
40030— Nontextile apparel & household goods
0.804
1.142
0.820
0.418
0.427
40040— Footwear of leather, rubber, or other materials
4.939
8.644
8.741
5.845
4.306
40050— Sporting & camping apparel and footwear & gear
9.108
0.942
0.392
2.958
2.179
40100— Medicinal, dental & pharmaceutical preparations
2.254
0.116
0.249
0.369
1.367
JULY/AUGUST 1994
40
P ro d u c t
1988
1989
1990
40110— Books, magazines & other printed material
3.030
5.387
3.712
1.521
1.906
40120—Toiletries & cosmetics
0.000
0.000
2.034
0.000
0.367
1992
1991
40140— Other products (notions, writing & art supplies)
1.579
1.194
1.538
1.601
1.598
41000— Furniture, household items, baskets
1.898
2.914
3.516
3.304
2.699
19.451
19.780
20.002
13.120
16.421
0.719
41010— Glassware and porcelain
41020— Cookware, chinaware, cutlery, house & garden wares
0.402
0.210
0.419
1.202
41030— Household & kitchen appliances
0.004
0.000
0.000
0.009
0.007
41040— Rugs & other textile floor covering
0.108
0.060
0.417
1.404
0.743
41050— Other (clocks, portable typewriters, other goods)
0.236
1.614
1.064
0.751
1.020
41100— Motorcycles & parts
2.011
1.968
1.052
2.383
1.825
41110— Pleasure boats & motors
0.000
0.000
0.064
0.011
0.000
41120— Toys, shooting & sporting goods & bicycles
1.734
0.499
0.535
0.676
1.337
41130— Photo & optical equipment
0.005
0.000
0.000
0.026
0.013
41140— Musical instruments & other recreational equipment
2.628
7.830
9.132
14.905
12.279
41210— Radios, phonographs, tape decks & other stereo
0.000
0.000
0.000
0.000
0.000
41220— Records, tapes & disks
0.580
2.122
6.494
2.147
1.460
41300— Numismatic coins
0.096
0.273
0.293
0.186
0.033
41310— Jewelry (watches, rings, etc.)
1.239
0.306
0.163
0.251
0.685
41320— Artwork, antiques, stamps and other collectibles
1.527
1.866
2.124
1.877
3.018
24.705
0.055
0.000
0.000
0.000
0.000
0.000
0.000
0.011
0.000
42000— Nursery stocks, cut flowers, Christmas trees
42100— Gem diamonds-uncut or unset
42110— Other gem stones-precious, semiprecious, & imitations
18.437
28.459
29.001
26.076
28.718
50000— Military aircraft & parts
0.000
0.000
0.000
0.072
0.223
50010— Other military equipment
0.000
1.168
2.261
2.980
3.917
50020— U.S. goods returned, & reimports
0.083
0.238
0.068
0.243
0.224
50030— Minimum value shipments
3.031
2.657
2.932
2.595
2.258
50040— Other (movies, miscellaneous imports & special transactions)
0.401
2.284
1.511
5.017
7.577
Index of Relative Comparative Advantage: Hungary
P ro d u c t
00000— Green coffee
1988
1989
1990
1 9 91
1992
0.000
0.097
0.000
0.000
0.000
00100— Meat, poultry & other edible animals
14.591
9.405
12.703
13.159
8.179
00110— Dairy products & eggs
11.418
19.675
14.758
19.731
21.707
00120— Fruits & preparations
6.771
10.356
10.951
12.691
8.122
00130— Vegetables & preparations
4.861
9.420
4.692
3.826
2.697
00140— Nuts & preparations
0.096
0.069
0.000
0.000
0.050
00150— Food oils & oilseeds
0.057
0.000
0.418
0.000
0.614
00160— Bakery & confectionery products
0.144
0.814
1.713
1.816
1.361
00170— Tea, spices & preparations
4.940
6.259
5.211
5.039
3.535
00180— Other (soft beverages, processed coffee, etc.)
2.051
2.679
1.673
1.157
0.271
00190— Wine & related products
1.393
1.778
1.993
2.197
2.516
00200— Feedstuff and foodgrains
0.819
1.749
1.310
1.441
5.223
01000— Fish & shellfish
0.000
0.001
0.026
0.000
0.000
01010— Alcoholic beverages, except wine
0.016
0.044
0.066
0.104
0.150
01020— Other nonagricultural foods & food additives
2.170
1.416
1.667
1.439
1.268
10010— Fuel oil
0.000
0.000
0.000
0.001
0.000
10020— Other petroleum products
0.179
0.303
0.177
0.190
0.234
0.069
0.014
10300— Nuclear fuel materials & fuels
RESERVE BANK OF ST. LOUIS
FEDERAL
0.000
0.000
0.056
41
Product
1988
1989
1990
1991
1992
11000— Pulpwood and woodpulp
0.004
0.000
0.000
0.000
0.000
0.010
11110— Paper & paper products, n.e.s.
0.021
0.027
0.004
0.000
12000— Cotton, wool & other natural fibers
1.253
2.597
0.465
1.331
1.180
12030— Hides & skins, & fur skins-raw
0.159
0.067
0.099
0.026
0.000
11.475
25.183
5.298
0.403
3.101
5.543
3.044
12060— Farming materials, including farm animals
12070— Other (tobacco, waxes, nonfood oils)
1.093
2.792
3.089
12100— Cotton cloth & fabrics, thread & cordage
9.846
6.120
4.046
1.343
1.325
12110— Wool, silk & other vegetable fabric
6.299
8.118
4.086
4.559
3.813
12135— Synthetic cloth & fabric, thread & cordage
6.093
4.726
2.439
1.953
1.364
0.047
12140— Other materials (hair, synthetics, etc.)
2.417
2.933
5.336
0.758
12150— Finished textile industrial supplies
5.273
2.070
3.206
1.927
2.001
12160— Leather & furs-unmanufactured
0.143
1.307
0.611
2.222
0.000
12320— Other materials, except chemicals
0.293
0.029
0.740
1.006
1.140
12500— Plastic materials
0.049
0.541
2.453
1.372
1.371
12510— Fertilizers, pesticides, and insecticides
0.000
0.007
0.000
0.789
1.679
12530— Industrial inorganic chemicals
2.253
1.391
1.542
1.481
1.621
12540— Industrial organic chemicals
0.476
1.137
1.234
0.750
1.171
0.203
12550— Other chemicals (coloring agents, print inks, paint)
3.683
0.737
0.653
0.575
13000— Lumber & wood in the rough
0.000
0.000
0.000
0.001
0.001
13010— Plywood & veneers
0.000
0.013
0.009
0.000
0.000
13020— Stone, sand, cement & lime
0.095
0.006
0.000
0.000
0.000
13100— Glass-plate, sheet, etc. (excluding automotive)
0.033
0.154
0.000
0.128
0.033
0.009
13110— Other-finished (shingles, molding, wallboard, etc.)
0.000
0.001
0.002
0.004
13120— Nontextile floor & wall tiles and other covering
0.000
0.000
0.012
0.088
0.000
14000— Steelmaking & ferroalloying materials
0.046
0.000
0.003
0.000
0.000
14100— Iron & steel mill products-semifinished
1.917
1.957
2.083
1.162
0.988
14200— Bauxite & aluminum
0.154
0.010
0.000
0.086
0.000
14220— Copper
0.000
0.000
0.000
0.000
0.040
14240— Nickel
0.000
0.296
0.145
0.000
0.000
14270— Nonmonetary gold
0.032
0.029
0.034
0.007
0.000
0.000
14280— Other precious metals
0.000
0.000
0.000
0.000
14290— Miscellaneous nonferrous
0.063
0.042
0.069
0.645
1.095
15000— Iron and steel products, except advanced manufacturers
0.076
0.238
0.003
0.003
0.138
15100— Iron and steel manufacturers, advanced
0.148
0.011
0.017
0.026
0.055
15200— Finished metal shapes, except steel
6.805
7.929
6.608
5.552
9.806
16040— Sulfur & nonmetallic minerals
0.549
0.205
0.203
0.091
0.000
16050— Other (synthetic rubber, wood, cork, gums, resins, etc.)
0.022
0.000
0.065
0.136
0.066
16110— Audio & visual tapes & other media
0.000
0.008
0.001
0.000
0.000
16120— Other (boxes, belting, glass, abrasives, etc.)
1.040
1.426
3.016
2.535
1.666
1.268
20000— Generators, transformers & accessories
0.003
0.075
0.180
0.522
20005— Electric apparatus & parts, n.e.c
0.449
0.787
0.640
0.897
1.295
21000— Drilling & oil field equipment & platforms
0.467
0.000
0.000
0.000
0.000
21010— Specialized mining & oil processing equipment
0.000
0.000
0.000
0.000
0.024
21030— Excavating, paving & construction machinery
0.202
0.014
0.191
1.150
0.113
21040— Nonfarm tractors & parts
0.639
1.689
0.340
0.025
3.454
21100— Industrial engines, pumps, compressors & generators
0.054
0.174
0.325
0.610
0.635
21110— Food & tobacco processing machinery
0.089
0.087
0.079
0.009
0.006
21120— Machine tools, metal working, molding & rolling
0.183
1.046
0.531
0.949
0.292
21130— Industrial textiles, sewing, & leather working machinery
0.031
0.000
0.010
0.016
0.176
21140— Woodworking, glass working, & plastic & rubber machinery
0.029
0.012
0.119
0.152
3.631
JULY/AUGUST 1994
42
P ro d u c t
1988
1989
1990
1991
21150— Pulp & paper machinery
0.002
0.015
0.010
0.600
0.371
21160— Measuring, testing & control instruments
0.254
0.314
0.212
0.193
0.671
21170— Materials handling equipment
0.138
0.332
0.289
0.514
0.322
21180— Other industrial machinery
1.301
1.588
1.846
0.908
0.963
21190— Photo & other service industry machinery
0.225
0.290
0.176
0.144
0.122
21200— Agricultural machinery and equipment
3.852
7.856
7.170
8.139
10.255
21300— Computers
0.000
0.001
0.003
0.002
0.001
21301— Computer accessories, peripherals & parts
0.000
0.007
0.004
0.013
0.006
21320— Semiconductors
0.007
0.001
0.009
0.003
0.030
21400—Telecommunications equipment
0.191
0.014
0.012
0.026
0.014
21500— Business machinery & equipment, except computers
0.010
0.290
0.141
0.079
0.030
21600— Laboratory, testing & control instruments
0.013
0.078
0.060
0.432
1.204
21610— Other scientific, medical & hospital equipment
0.071
0.172
0.075
0.113
0.163
22000— Civilian aircraft, complete - all
0.009
0.003
0.009
0.004
0.011
1992
22010— Parts for civilian aircraft
0.000
0.005
0.019
0.033
0.010
22020— Engines for civilian aircraft
0.000
0.000
0.000
0.000
0.096
22100— Railway transportation equipment
0.086
0.000
0.174
0.512
0.010
22210— Other commercial vessels, new and used
0.000
0.000
0.000
0.698
0.000
22220— Marine engines & parts
0.000
0.000
0.000
0.000
0.011
30100— Trucks, buses, & special purpose vehicles
0.000
0.005
0.000
0.095
0.001
30110— Bodies & chassis for trucks & buses
0.001
2.774
15.454
29.076
9.517
30200— Engines & engine parts
0.026
0.002
0.004
0.001
0.001
30220— Automotive tires & tubes
5.801
5.468
4.798
1.667
0.643
30230— Other parts & accessories
2.261
2.303
2.417
2.601
2.921
40000— Apparel & household goods-cotton
1.245
1.688
1.715
1.646
1.972
21.349
40010— Apparel & household goods-wool
17.527
18.727
14.530
13.901
40020— Apparel & household goods-other textiles
2.414
2.043
1.512
1.472
1.920
40030— Nontextile apparel & household goods
1.054
1.365
1.937
0.293
0.333
40040— Footwear of leather, rubber, or other materials
4.334
2.658
4.401
3.076
2.342
40050— Sporting & camping apparel, footwear & gear
0.467
0.364
0.448
0.614
0.516
40100— Medicinal, dental & pharmaceutical preparations
5.698
5.677
6.617
4.566
3.644
40110— Books, magazines & other printed material
0.586
0.458
0.303
0.741
0.153
40120— Toiletries & cosmetics
0.059
0.039
0.016
0.172
0.060
40140— Other products (notions, writing & art supplies)
0.071
0.583
0.375
0.323
0.258
41000— Furniture, household items, baskets
2.028
2.181
1.558
1.816
0.929
41010— Glassware and porcelain
4.854
6.253
6.242
7.284
9.624
41020— Cookware, chinaware, cutlery, & other household goods
0.919
1.953
1.018
1.209
1.365
41030— Household & kitchen appliances
0.011
0.000
0.006
0.028
0.005
41040— Rugs & other textile floor covering
0.652
0.557
0.914
0.709
0.704
41050— Other (clocks, portable typewriters, other household goods)
6.246
2.651
2.073
2.936
1.817
41100— Motorcycles & parts
0.000
0.054
0.000
0.000
0.000
41110— Pleasure boats & motors
0.164
0.588
0.174
0.007
0.123
41120— Toys, shooting & sporting goods, & bicycles
0.100
0.086
0.137
0.965
1.794
41130— Photo & optical equipment
0.000
0.253
0.215
0.159
0.149
41140— Musical instruments & other recreational equipment
0.300
0.352
0.102
0.318
0.315
41200— Television receivers, vers & other video equipment
0.000
0.000
0.000
0.000
0.000
41210— Radios, phonographs, tape decks & other stereo
0.000
0.000
0.001
0.003
0.000
41220— Records, tapes & disks
2.405
1.617
2.066
1.810
1.391
41300— Numismatic coins
0.059
0.078
6.805
0.668
0.223
41310— Jewelry (watches, rings, etc.)
0.108
0.070
0.048
0.007
0.000
Digitized forFEDERAL
FRASER RESERVE BANK OF ST. LOUIS
43
Product
1988
1989
41320— Artwork, antiques, stamps and other collectibles
0.664
42000— Nursery stocks, cut flowers, Christmas trees
0.000
42100— Gem diamonds-uncut or unset
0.017
0.000
42110— Other gem stones-precious, semiprecious & imitation
0.000
0.016
1992
1990
1991
0.695
1.063
4.373
1.429
0.003
0.055
0.205
0.246
0.000
0.000
0.000
0.004
0.000
0.000
50000— Military aircraft & parts
0.000
0.000
0.000
0.000
0.008
50010— Other military equipment
3.655
3.570
2.698
2.423
4.116
50020— U.S. goods returned, & reimports
0.106
0.090
0.070
0.224
0.129
50030— Minimum value shipments
0.511
0.364
0.380
0.401
0.378
50040— Other (movies, miscellaneous imports & special transactions)
0.603
0.577
3.002
0.050
1.433
Index of Relative Comparative Advantage: Poland
Product
1988
1989
1990
1991
1992
00000— Green coffee
0.000
0.025
0.000
0.000
0.000
0.000
0.000
0.072
0.000
0.000
38.943
37.600
25.330
11.456
8.119
00110— Dairy products & eggs
6.980
13.598
7.710
11.218
21.245
00120— Fruits & preparations
1.227
2.234
2.184
4.453
3.546
00130— Vegetables & preparations
0.803
1.038
1.214
1.788
1.298
00150— Food oils & oilseeds
0.490
2.364
18.895
0.677
0.548
00020— Cane and beet sugar
00100— Meat, poultry & other edible animals
00160— Bakery & confectionery products
1.024
1.522
1.335
2.500
3.081
00170— Tea, spices & preparations
0.941
0.104
0.509
0.014
0.192
00180— Other (soft beverages, processed coffee, etc.)
0.905
0.957
1.090
0.570
2.039
00190— Wine & related products
0.096
0.122
0.074
0.193
0.296
00200— Feedstuff and foodgrains
7.577
0.153
0.024
4.586
4.428
01000— Fish & shellfish
2.261
2.057
4.079
3.731
1.579
01010— Alcoholic beverages, except wine
0.151
0.263
1.560
1.573
0.623
01020— Other nonagricultural foods & food additives
0.612
0.000
0.000
0.000
0.000
10010— Fuel oil
0.000
0.000
0.000
0.000
0.408
10020— Other petroleum products
0.000
0.000
0.000
0.000
0.000
10100— Coal & other fuels, except gas
0.000
36.870
0.000
0.000
0.139
10300— Nuclear fuel materials & fuels
0.000
0.000
0.000
0.023
0.000
11000— Pulpwood and woodpulp
0.000
0.000
0.000
0.000
0.000
11110— Paper & paper products, n.e.s.
0.002
0.047
0.002
0.000
0.001
12030— Hides & skins, & fur skins-raw
0.566
0.795
0.593
1.845
2.689
12050— Natural rubber & similar gums
0.000
0.000
0.000
0.000
0.000
9.954
2.174
2.867
1.913
2.326
14.229
8.507
9.420
10.847
14.617
12060— Farming materials, including farm animals
12070— Other (tobacco, waxes, nonfood oils)
12100— Cotton cloth & fabrics, thread & cordage
2.222
0.634
1.167
1.794
0.672
12.146
15.070
19.067
27.927
34.972
1.011
1.782
2.071
2.919
2.880
44.130
0.559
0.000
0.000
0.000
12150— Finished textile industrial supplies
0.001
0.676
0.051
0.010
0.000
12160— Leather & furs-unmanufactured
0.000
0.094
0.324
0.092
0.104
12110— Wool, silk & other vegetable fabric
12135— Synthetic cloth & fabric, thread & cordage
12140— Other materials (hair, synthetics, etc.)
12320— Other materials, except chemicals
0.028
2.298
0.000
0.002
0.016
12500— Plastic materials
0.016
0.016
0.034
0.015
0.148
12510— Fertilizers, pesticides, and insecticides
0.002
0.131
0.000
1.959
2.332
12530— Industrial inorganic chemicals
0.624
0.470
1.738
2.921
0.974
12540— Industrial organic chemicals
0.445
0.731
0.263
0.513
0.250
JULY/AUGUST 1994
44
Product
1988
12550— Other chemicals (coloring agents, print inks, paint)
2.636
13000— Lumber & wood in the rough
0.000
13010— Plywood & veneers
0.734
13020— Stone, sand, cement & lime
1989
1990
1991
1992
1.089
1.319
4.231
4.385
0.000
0.000
0.000
0.000
0.000
0.090
0.741
3.899
0.000
0.000
0.000
0.021
0.000
13100— Glass-plate, sheet, etc. (excluding automotive)
0.084
0.000
1.746
1.788
0.931
13110— Other-finished (shingles, molding, wallboard, etc.)
0.000
1.413
0.387
0.000
0.005
13120— Nontextile floor & wall tiles and other covering
0.000
0.002
0.000
0.000
0.000
14000— Steelmaking & ferroalloying materials
0.000
0.000
0.194
0.000
0.580
14100— Iron & steel mill products-semifinished
3.339
3.309
2.773
4.461
1.915
14200— Bauxite & aluminum
0.151
0.090
0.088
0.178
0.000
14220— Copper
6.709
13.997
0.000
0.000
0.018
14240— Nickel
0.550
0.000
0.637
0.000
0.000
14260—Zinc
6.233
0.017
1.277
0.020
1.756
14270— Nonmonetary gold
0.000
0.000
0.000
0.030
0.000
14280— Other precious metals
0.000
0.000
0.000
0.002
0.000
14290— Miscellaneous nonferrous
0.099
0.000
0.006
0.187
0.000
15000— Iron and steel products, except advanced manufacturers
3.122
2.625
2.380
2.249
1.404
15100— Iron and steel manufacturers, advanced
1.122
1.831
1.563
2.255
1.311
15200— Finished metal shapes, except steel
2.742
4.467
6.841
8.239
9.644
16040— Sulfur & nonmetallic minerals
0.164
0.054
0.026
0.004
0.018
16050— Other (synthetic rubber, wood, cork, gums, resins, etc.)
0.084
0.010
0.549
0.328
0.163
16110— Audio & visual tapes & other media
0.000
0.000
0.020
0.000
0.000
16120— Other (boxes, belting, glass, abrasives, etc.)
0.430
0.120
0.182
0.401
0.199
20000— Generators, transformers & accessories
0.375
0.647
0.527
1.216
0.443
20005— Electric apparatus & parts, n.e.c
0.008
0.276
0.433
0.544
0.892
21000— Drilling & oil field equipment & platforms
0.772
0.052
0.017
0.057
0.202
21010— Specialized mining & oil processing equipment
0.000
0.000
0.000
0.219
0.291
21030— Excavating, paving & construction machinery
0.284
0.191
0.168
0.078
0.520
34.255
15.577
22.543
27.693
12.064
21100— Industrial engines, pumps, compressors & generators
0.497
0.168
0.318
0.490
0.773
21110— Food & tobacco processing machinery
0.054
0.186
0.292
0.400
1.063
21120— Machine tools, metal working, molding & rolling
3.013
3.118
4.097
4.574
4.903
21130— Industrial textiles, sewing, & leather working machinery
0.011
0.103
0.024
0.074
0.000
21140— Woodworking, glass working, & plastic & rubber machinery
0.148
0.319
0.742
0.710
0.570
21150— Pulp & paper machinery
0.034
0.122
0.032
0.056
0.148
21160— Measuring, testing & control instruments
0.151
0.461
0.631
0.686
0.632
21170— Materials handling equipment
1.264
0.922
0.526
0.674
0.140
21180— Other industrial machinery
0.249
0.936
1.224
1.311
2.106
21190— Photo & other service industry machinery
0.757
0.687
0.841
0.709
0.739
21200— Agricultural machinery and equipment
2.403
4.637
7.728
7.220
10.719
21040— Nonfarm tractors & parts
21300— Computers
0.000
0.000
0.001
0.013
0.000
21301— Computer accessories, peripherals & parts
0.006
0.000
0.005
0.018
0.011
21320— Semiconductors
0.000
0.000
0.024
0.050
0.043
21400— Telecommunications equipment
0.010
0.010
0.069
0.028
0.010
21500— Business machines & equipment, except computers
0.025
0.142
0.093
0.189
0.076
0.342
21600— Laboratory, testing & control instruments
0.197
0.209
0.138
0.120
21610— Other scientific, medical & hospital equipment
0.095
0.103
0.037
0.083
0.226
22000— Civilian aircraft, complete - all
0.858
0.678
0.610
0.362
0.210
22010— Parts for civilian aircraft
0.334
0.154
0.146
0.223
0.008
22020— Engines for civilian aircraft
1.080
0.815
0.883
0.665
0.583
Digitized forFEDERAL
FRASER RESERVE BANK OF ST. LOUIS
45
Product
1988
1989
1990
1991
1992
22100— Railway transportation equipment
0.000
0.107
0.753
2.995
4.603
22210— Other commercial vessels, new and used
0.000
0.000
0.198
0.000
0.000
22220— Marine engines & parts
0.000
0.007
0.000
0.021
0.000
0.000
30000— Passenger cars complete & assembled (new and used)
0.001
0.000
0.000
0.000
30100— Trucks, buses, & special purpose vehicles
0.349
0.357
0.376
0.335
0.214
30110— Bodies & chassis for trucks & buses
0.000
0.000
0.000
0.094
0.000
30200— Engines & engine parts
0.014
0.159
0.233
0.177
0.212
30220— Automotive tires & tubes
0.000
0.000
0.125
0.855
0.660
30230— Other parts & accessories
0.023
0.035
0.028
0.040
0.096
40000— Apparel & household goods-cotton
2.692
2.802
3.593
2.109
1.981
40010— Apparel & household goods-wool
7.677
7.618
7.535
8.635
14.474
40020— Apparel & household goods-other textiles
1.284
0.952
1.330
1.527
1.384
40030— Nontextile apparel & household goods
0.176
0.098
0.301
0.074
0.040
40040— Footwear of leather, rubber, or other materials
1.138
1.699
1.178
1.891
2.439
40050— Sporting & camping apparel, footwear & gear
0.571
0.253
0.151
0.187
0.456
40100— Medicinal, dental & pharmaceutical preparations
1.728
1.006
0.293
0.485
0.435
40110— Books, magazines & other printed material
0.122
0.118
0.150
0.059
0.174
40120—Toiletries & cosmetics
0.055
0.025
0.032
0.012
0.046
40140—Other products (notions, writing & art supplies)
0.010
0.014
0.069
0.094
0.078
41000— Furniture, household items, baskets
2.617
2.883
3.681
3.452
2.989
41010— Glassware and porcelain
5.992
14.285
19.087
25.244
28.039
41020— Cookware, chinaware, cutlery, & other household goods
0.745
0.489
0.720
0.437
0.330
41030— Household & kitchen appliances
0.120
0.116
0.553
1.337
1.084
41040— Rugs & other textile floor covering
0.295
0.053
0.170
0.135
0.166
41050— Other (clocks, portable typewriters, other household goods)
2.462
1.848
2.991
3.058
2.453
0.071
41100— Motorcycles & parts
0.000
0.002
0.000
0.000
41110— Pleasure boats & motors
0.048
0.076
0.297
0.000
0.009
41120— Toys, shooting & sporting goods, & bicycles
0.448
0.488
0.507
0.316
0.385
41130— Photo & optical equipment
0.000
0.044
0.052
0.043
0.052
41140— Musical instruments & other recreational equipment
0.015
0.007
0.071
0.407
0.160
41200—Television receivers, vers & other video equipment
0.000
0.000
0.000
0.000
0.029
41210— Radios, phonographs, tape decks & other stereo
0.000
0.000
0.007
0.007
0.014
41220— Records, tapes & disks
0.160
0.066
0.125
0.380
0.505
41300— Numismatic coins
6.560
1.878
0.112
0.807
0.975
41310—Jewelry (watches, rings, etc.)
0.014
0.034
0.092
0.112
0.144
41320— Artwork, antiques, stamps and other collectibles
0.084
0.674
0.234
0.309
0.365
42000— Nursery stocks, cut flowers, Christmas trees
1.269
0.000
0.061
0.042
0.380
42100— Gem diamonds-uncut or unset
0.000
0.000
0.024
0.000
0.000
42110— Other gem stones-precious, semiprecious & imitation
0.050
0.022
0.044
0.103
0.191
50000— Military aircraft & parts
0.004
0.000
0.163
0.221
1.420
50010— Other military equipment
0.105
0.000
0.130
0.311
0.373
50020— U.S. goods returned, & reimports
0.422
0.462
0.332
0.412
0.515
50030— Minimum value shipments
0.727
0.567
0.535
0.535
0.728
50040— Other (movies, miscellaneous imports & special transactions)
0.372
0.170
0.728
0.246
1.640
JULY/AUGUST 1994
47
John C. W eicher
John C. Weicher is a senior fellow at the Hudson Institute and
a visiting scholar at the Federal Reserve Bank o f St. Louis.
Heidi L. Beyer provided research assistance.
The New Structure of the
Housing Finance System
A,
. FTER 25 YEARS OF ECONOMIC evolution
and 15 years of political turmoil, the U.S. housing
finance system has changed in fundamental ways,
and the structure of the new system is becoming
apparent. The system is still intended to allocate
credit to housing and hold mortgage rates below
their free-market level, but this subsidy is provided
through different institutional arrangements. The
dominant institutions are now extremely large
government-sponsored enterprises (GSEs] which
operate in the secondary mortgage market, issuing
securities that are backed by mortgages and buying
mortgages originated by other institutions. They
have taken the place of small local savings and
loan associations which make loans directly to
homebuyers and hold the mortgages in their own
portfolios. The cost of the subsidy falls on tax
payers who bear the risk of failure by the GSEs.
The public purpose of government intervention
in the housing finance system has always been to
promote homeownership, giving force to a social
preference that derives from a widely held but
rarely analyzed belief that homeowners are better
citizens, because they “have a stake in society.”
Subsidies are appropriate because families will
not take this social benefit into account in deciding
whether to buy a home. The system also has two
subsidiary goals: (1) countercyclical support for
housing production; and (2) geographic equity
(as defined by public policy) in the mortgage
market. The latter is more directly related to the
purpose of promoting homeownership.
Achieving these purposes is the responsibility
mainly of privately owned institutions which are
supposed to meet them while maximizing profit
and avoiding direct cost to taxpayers. This is also
true of the major housing finance agencies within
the federal government; they do not normally
receive funds from the U.S. Treasury. The private
as well as public institutions operate under
statutes which define their powers, limitations
and privileges, and delineate what they can hold
as assets and liabilities. To some extent, they
compete against each other.
The home mortgage market consists of some
$3 trillion of household debt, nearly all of it
held by private institutions, of which more than
$1 trillion is explicitly or im plicitly guaranteed
by the federal government (not counting deposit
insurance). There is continuing tension between
the public purposes of the system and the safety
and soundness— and profits— of the privately
owned institutions that predominate in it.
This paper first describes the present structure
of the housing finance system, contrasting it with
the traditional system and explaining why the
system has changed. It concludes with a discus
sion of the major issues that will face public policy
over the next few years.
JULY/AUGUST 1994
48
THE CURRENT SYSTEM
Mortgage and Housing Markets
The mortgage market has traditionally been
separate from other capital markets, because
mortgages differ in key respects from other debt
instruments. A home mortgage is a loan to an
individual or couple for the purpose of buying
a particular house. The amount the lender is
willing to loan depends on the value of the prop
erty. The mortgagor promises to repay the loan
over time. If he or she fails to do so, thus default
ing on the mortgage, the lender can foreclose,
take title to the property, and sell it to someone
else. The default risk (also termed credit risk)
depends on changes in the value of the property
and in the circumstances of the owner, such as
job loss, divorce, or the death of a husband or
wife. The extent of loss in the event of default
depends on changes in property values. Real
estate markets are local markets, so evaluating
a particular piece of property requires local
expertise. For these reasons, mortgages have
traditionally been illiquid; investors have been
willing to buy them only if they have the knowl
edge required to evaluate them.
The standard mortgage instrument—until the
1980s, almost the only mortgage instrument—is
a fixed-rate, level-payment, long-term, self-amor
tizing loan. The term usually runs for 30 years.
Such mortgages carry prepayment risk as well as
default risk. The term can be shortened only at
the option of the borrower, by prepaying the loan.
If market interest rates fall, as happened most
recently during 1993-94, mortgagors are likely
to prepay their loans and refinance their homes
at a lower interest rate. If rates rise, mortgagors
are unlikely to prepay unless they are moving,
and lenders will find themselves earning belowmarket rates on their mortgage portfolios. Thus,
lenders bear the risk of adverse movements in
interest rates. This was a particular problem
during the inflation of the late 1970s. As a result,
mortgages with adjustable rates (ARMs) were
authorized and became common in the early
1980s. A variety of other new instruments also
have come into existence, such as balloon mort
gages, which are not fully amortized over their
term, and graduated payment mortgages, which
carry fixed interest rates but have lower payments
in the early years. The traditional standard
mortgage remains the most common, although
its popularity relative to ARMs has varied as
interest rates have fluctuated. Fixed-rate mort
gages are more popular among borrowers when
Digitized for FEDERAL
FRASER RESERVE BANK OF ST. LOUIS
the general level of interest rates is low and
ARMs are more popular when the level is high.
The dominant position of the standard mort
gage developed under the auspices of the federal
government, specifically the Federal Housing
Administration (FHA), which was created in the
1930s to insure home mortgages. Buyers pay a
mortgage insurance premium to FHA, and in
return FHA guarantees that lenders w ill receive
payment of the outstanding principal balance on
the mortgage in the event of default and foreclo
sure. FHA is required by law to operate on an
actuarially sound basis; its insurance premiums
are supposed to cover its losses and operating
costs. Once FHA demonstrated the viability and
profitability of such mortgages, the “FHA mort
gage” also became the norm for conventional
mortgages (those not insured or guaranteed by a
government agency).
Primary Lenders
The local nature of real estate markets has
meant that mortgage lenders have traditionally
been local institutions. The most important
have been the savings and loan associations
(S&Ls), both in terms of their share of the mort
gage market and the share of mortgages in their
portfolios. The S&Ls started as local specialized
mortgage portfolio lenders, obtaining deposits
from “small savers” within their locality and
making mortgage loans there also. Until 1983
their lending areas were geographically limited
by statutes and regulation. Typically, their
deposits have been locally generated as well,
though there has been no geographic limitation
on liabilities. Mutual savings banks, concentrat
ed in the Northeast, are similar to S&Ls as spe
cialized mortgage portfolio lenders, but they
developed independently and started with a dif
ferent purpose: to provide a range of financial
services to households. Savings banks and S&Ls
together are usually termed “thrifts.” They have
access to the national capital markets through
the Federal Home Loan Bank System, a set of 12
regional Federal Home Loan Banks which they
own. Chartered and regulated by the federal
government, the Home Loan Banks are able to
borrow at preferential rates in the capital mar
kets. Commercial banks also hold a significant
share of home mortgages, but mortgages com
prise a minor fraction of their assets. Until 1989
they could not belong to the Home Loan Bank
System; they now can if their mortgage holdings
are large enough.
49
S&Ls, mutual savings banks and commercial
banks are primary lenders; they originate mort
gages which they hold in their own portfolios.
A large number of mortgages, however, are origi
nated by mortgage bankers, for immediate sale
in the secondary market to an investor who
expects to hold them. Mortgage bankers make
their money from fees for originating mortgages
and often for servicing them, collecting the
monthly payments and transmitting them to
the investor. Mortgage banking developed as
an important component of the housing finance
system when FHA began to insure mortgages.
FHA insurance and its uniform national under
writing standards meant that specialized knowl
edge of local housing markets was less important
for investors. Mortgage bankers have since
developed the skills necessary to originate
conventional mortgages and now originate
just under half of all home mortgages.
Securitization and the GovernmentSponsored Enterprises
The limitations of mortgages as investment
vehicles led to the creation of mortgage-backed
securities (MBSs) beginning in 1970. Mortgage
securitization consists of combining a group of
mortgages into a pool and selling shares in the
pool to investors. This spreads the risk of default
over a number of mortgages and allows investors
to calculate the probability of default for the
mortgages in the pool with more accuracy than
for any individual mortgage. The earliest and
simplest M BSs are known as pass-through secu
rities; the servicer collects principal and interest
payments and passes them through, without
taxation, to the investor.
The pass-through security does not reduce
prepayment risk. More recent forms, the
Collateralized Mortgage Obligation (CMO) and
the Real Estate Mortgage Investment Conduit
(REMIC), partition the principal cash flow from
a pool of mortgages or MBSs into maturity class
es, or tranches. Each investor receives a propor
tionate share of all interest payments. Principal
payments are allocated in full as they occur to
each tranche in turn, starting with the shortestmaturity tranche. Tranches are separately
priced and sold to investors with different time
horizons. Investors in the longer-term tranches
1 The collateral for CMOs and REMICs can be either whole
mortgages or MBSs. Thus, the ratio of CMOs and REMICs
to all MBSs does not represent either their share of all MBSs
or their share of all securitized mortgages.
incur greater interest rate risk, but have some
protection against prepayment. They are not,
however, protected in the event of a protracted
decline in interest rates; if mortgagors prepay in
large numbers, the securities will be redeemed.
This type of security was developed in 1983 and
it now accounts for about half of all mortgages
that are securitized.1
Securitization has broadened the mortgage
market by creating instruments that appeal to
investors without special knowledge of local
housing markets. The payment streams are sim
ilar to bonds, and the consequences of default
and prepayment are minimized.
Until the last few years, the market for MBSs
has generally required a government guarantee
on the mortgages, the securities, or both.
Securitization was developed by a government
agency, the Government National Mortgage
Association (GNMA or Ginnie Mae). GNMA
issued pass-through securities based on pools
of FHA-insured mortgages, and added its own
guarantee of timely payment of principal and
interest to the FHA guarantee of principal pay
ment in case of default. (GNMA also issues
securities backed by pools of mortgages guaran
teed by VA, originally the Veterans
Administration and now the Department of
Veterans Affairs, in a program created after
World War II and modeled on FHA.)
The other major MBS guarantors are the housing
GSEs: the Federal National Mortgage Association
(FNMA or Fannie Mae) and the Federal Home
Loan Mortgage Corporation (FHLMC or Freddie
Mac).2 Both also buy and hold mortgages in their
own portfolios, financing them by issuing debt
securities in the capital markets, and in fact they
have the first- and fourth-largest mortgage port
folios, respectively, of all mortgage lenders in the
United States. They are secondary market agen
cies; they do not originate mortgages but buy
loans from primary lenders or mortgage bankers.
FNMA and FHLMC are privately owned insti
tutions with stockholders and private boards,
but they are federally chartered corporations
with a variety of special privileges, and the
President appoints five members out of 18 to the
board of each one. The most important of the
privileges are exemption from state and local
2 GNMA can also be considered a GSE, but it is fully owned
by the federal government and operates as an agency within
HUD, as is FHA.
JULY/AUGUST 1994
50
income taxes, exemption from Securities and
Exchange Commission registration and state
securities laws, the ability to borrow $2.25 bil
lion from the U.S. Treasury in an emergency,
and the fact that their debt securities are “quali
fied investments” for regulated financial institu
tions. Their securities are also issuable and
payable through Federal Reserve Banks.3
These privileges give them “agency status” in
the capital markets, a general perception that the
government w ill stand behind them. This per
ception is reinforced by the fact that both are
very large financial institutions, “too big to fail.”
Agency status allows them to borrow at relatively
low rates and to issue or guarantee payment on
securities based on pools of conventional mort
gages. The market treats their guarantees of
timely payment of principal and interest as
equivalent to a government guarantee.4
The Role o f the F ed era l Government
It should be clear that the federal government
has a large role in the housing finance system. It
insures some mortgages; it issues securities
backed by pools of those mortgages; and it has
chartered corporations which are believed in the
capital markets to have an im plicit government
guarantee behind their debt securities and their
mortgage securities. In addition, it regulates and
insures the deposits of primary lenders, and has
chartered institutions which provide them with
access to the capital markets. The federal gov
ernment is generally credited with conducting
three successful social experiments in the mort
gage market: demonstrating the feasibility of
long-term, self-amortizing loans; mortgage insur
ance; and securitization. In all three cases, the
private sector has successfully copied the feder
al models. The FHA mortgage became the stan
dard for conventional mortgages, and a private
mortgage insurance industry has developed to
insure them. The private sector now accounts
for more business than the federal government
in both instances. The demonstration that secu
ritization is feasible has been followed by a sub
3 Most of these privileges date back in some form to the
FNMA Charter Act of 1954 or its initial 1938 charter. In 1970
the same privileges were extended to FHLMC when it was
created.
4 The securities may be issued directly by a GSE or alterna
tively by a subsidiary of a private entity such as a Wall Street
firm, with the GSE guaranteeing the timely payment of prin
cipal and interest.
5 These statements are based on unpublished tabulations of
FHA-insured loans between 1989 and 1992. The tabula-
Digitized for FEDERAL
FRASER RESERVE BANK OF ST. LOUIS
stantial volume of private M BS activity only
since about 1990, however, and private securi
ties are still a small part of the total market.
The Dividing Lines
The federal government also demarcates the
market segments of the various institutions by
means of two statutory numerical concepts: the
FHA ceiling and the conforming loan limit.
The FHA ceiling is the maximum principal
balance on a mortgage that FHA can insure. The
ceiling is set in law in nominal dollars; since
1980 higher amounts have been allowed in areas
with higher housing costs. The present ceiling
is $67,500, or 95 percent of the area median
home price if that is higher, up to a maximum of
$151,725. The maximum is still less than 95
percent of the area median home price in a num
ber of large markets, among them New York and
the largest metropolitan areas on the West Coast,
and it is raised every few years.
FHA insurance is intended for the first-time
homebuyer who can only afford a relatively
small down payment, and who thus poses a
greater risk of default to the lender. Most FHA
buyers make a down payment of five percent or
less.5 Below the ceiling, nearly all low down
payment loans are insured by FHA and securi
tized by GNMA.
The conforming loan limit is the maximum
principal amount of a mortgage that FNMA and
FHLMC can buy. Before 1974, they were
restricted to mortgages with principal amounts
below the FHA ceiling. A higher limit was set
by statute in that year. In 1977 the limit was set
at 25 percent above the maximum mortgage
amount for S&Ls, and both were raised in 1979.
After the S&L maximum was abolished in 1980,
the conforming loan limit was set by statute at
its then-current value of $93,750, and indexed
on the basis of the annual percentage change in
the mean price of homes bought with conven
tional mortgages. Since 1980, the limit has been
about 37 percent above the mean price. In 1993
tions differ from published data because FHA allows part
(before 1991, all) of the closing costs to be financed in the
mortgage, as is discussed in Price Waterhouse (1990, pp.
18-19). The published data do not adjust the loan-to-value
ratios to reflect financing of closing costs, and therefore
show somewhat lower loan-to-value ratios. For example,
Price Waterhouse (1990, p. 17), reports that in 1988-89
slightly less than half of FHA-insured mortgagors had loanto-value ratios above 95 percent.
51
the conforming loan limit was $203,150, while
the mean price was $144,000.6
Because of their agency status and the perception
that they are too big to fail, the GSEs can offer
lower interest rates than the S&Ls and therefore
dominate the market below the conforming loan
limit. Estimates of their cost advantage are in
the range of 20 to 35 basis points.7
The S&Ls remain as portfolio lenders above the
conforming loan limit. Below the limit, they
operate largely as mortgage bankers. They origi
nate mortgages not for their own portfolios but
for sale to the GSEs, although they may buy back
the securities issued on a pool of the mortgages
that they have sold. Regulations issued under
the Financial Institutions Reform, Recovery and
Enforcement Act of 1989 (FIRREA) gave the
S&Ls an incentive to move away from portfolio
lending by setting capital requirements only 40
percent as high against MBSs issued by the
GSEs as against whole mortgages. Other thrifts
and commercial banks have a similar role.
The mortgage market, therefore, can be divided
into the FHA/ GNMA submarket, for low down
payment loans below the FHA ceiling; the GSE
submarket, for most other loans below the con
forming loan limit; and the “jumbo” submarket,
occupied by S&Ls, other thrifts and commercial
banks, for loans above the conforming loan limit.
mortgages that were above the lim it when issued
may be below it a few years later. Thus, the
share of the market open to the GSEs is larger
when measured in terms of all outstanding
mortgages than it is when measured in terms of
mortgages originated in the current year.
Primary lenders do make loans below the con
forming loan limit. Some are nonstandard loans
which the GSEs do not choose to purchase, but
mortgages above as well as below the limit are
likely to be underwritten to the guidelines of the
GSEs, to keep open the option of selling them in
the secondary market.
In addition, the conforming loan limit appar
ently only adjusts in one direction. Declining
house prices during 1993 resulted in a reduction
of $6,050 in the calculated conforming loan
limit for 1994, as reported by the Federal
Housing Finance Board. FNMA and FHLMC
announced that they would not lower the limit,
because the 1980 statute referred only to
“increases,” and not to “decreases” or
“changes.”8 HUD Secretary Henry Cisneros, as
GSE regulator, first challenged this action and
then accepted it.
THE GROWING DOMINANCE OF
THE GSEs
Actual market segmentation, however, is less
clear-cut than the dollar demarcations suggest.
The FHA ceiling only applies to FHA. The
GSEs, the S&Ls and any other lender can originate
mortgages below the ceiling, and some such loans
are made. To some extent, the private mortgage
insurers compete with FHA by offering insurance
on loans with low down payments, though they
do not insure a large share of these mortgages.
The GSEs have been the thriving and expand
ing institutions in the system. In 1992, the latest
year for which full data are available, FHA and
VA loans were about 10 percent of the total dol
lar volume of all home mortgages issued, nonconforming loans about 20 percent, and conven
tional conforming loans about 70 percent. The
dominant role of FNMA and FHLMC in the con
forming loan market is reflected by the fact that
they securitized over half of these loans and
added to their mortgage portfolios as well.
Similarly, the conforming loan limit applies
only to the GSEs. The S&Ls and other primary
lenders can make loans below the limit. But the
conforming loan limit is much less restrictive on
the GSEs than the FHA ceiling is on FHA. Since
house prices in most years rise at least modestly,
The growth of the GSEs is shown in Table 1,
which depicts the mortgage market in terms of
the total dollar volume of loans outstanding at
various dates. The GSEs now hold or securitize
about 30 percent of the total, compared to about
7 percent in 1980. Since 1980 they have accounted
6 The annual adjustment is based on the percentage change
in prices of homes sold during the last five business days in
October.
8 The staff director of the Senate Housing Subcommittee as of
1980 has stated that the intent of the statute was that the
limit should move in accord with house prices in both direc
tions, but prices had risen so long and so much by 1980 that
nobody remembered the possibility of a decrease when the
bill was written.
7 See, for example, ICF (1990) and Hendershott and Shilling
(1989). The former estimates a differential of 23 basis
points as of 1987, the latter 30 to 35 basis points as of 1986.
Both apply to loans that are at least 15 percent above the
conforming loan limit and, therefore, unlikely to be sold in
the secondary market when they are seasoned. These are
apparently the most recent analyses.
JULY/AUGUST 1994
52
Table 1
Single-Family Mortgage Debt Outstanding, 1968-92 (end-of-year values)
Dollar Values (billions of current dollars)
1968
Portfolio lending
FNMA portfolio
FHLMC portfolio
S&Ls
Commercial banks
Others*
Subtotal
7
0
110
39
109
265
1980
52
4
411
160
1989
91
18
512
1992
124
31
375
452
229
856
336
529
1486
0
0
0
0
27
20
63
110
200
129
592
921
1380
0
0
0
0
0
265
0
14
92
4
110
965
220
266
358
77
921
2408
436
402
411
132
1380
2954
591
1573
Security holdings**
S&Ls
Commercial banks
Others*
Subtotal
Securities issued**
FNMA MBSs
FHLMC PCs
GNMA MBSs
Private pools
Subtotal
Total
Percent Shares
159
307
914
1968
1980
1989
1992
2.6
0.0
41.5
14.7
41.1
100.0
5.4
0.4
42.6
16.6
23.7
88.7
3.8
0.7
21.3
14.0
4.2
1.0
12.7
15.3
22.0
61.7
20.0
53.3
Security holdings**
S&Ls
Commercial banks
Others*
Subtotal
0.0
0.0
0.0
0.0
2.8
1.9
6.5
11.4
8.3
5.4
24.6
38.2
5.4
10.4
31.0
46.7
Securities issued**
FNMA MBSs
FHLMC PCs
GNMA MBSs
Private pools
Subtotal
0.0
0.0
0.0
0.0
0.0
0.0
1.5
9.5
0.4
11.4
9.1
11.1
14.9
14.8
13.6
13.9
4.5
46.7
Portfolio lending
FNMA portfolio
FHLMC portfolio
S&Ls
Commercial banks
Others*
Subtotal
3.2
38.2
* Others include mutual savings banks, life insurance companies, finance companies, the Farmers Home Administration, the
Federal Housing Administration, the Veterans Administration (Department of Veterans Affairs in 1989 and later), mortgage
companies, real estate investment trusts, state and local credit agencies, state and local retirement funds, noninsured pension
funds, credit unions, other U.S. government agencies, and individuals.
** Security holdings show the distribution of securities issued. Either can be added to portfolio lending data to obtain the totals;
both cannot be added without double counting. Security holdings can be added to data on portfolio lending to show mortgage
market activity of thrifts, banks and other institutions; securities issued can be added to data on portfolio lending to show mort
gage market activity of the GSEs.
SOURCES: Board of Governors; U.S. Department of Housing and Urban Development; Inside Mortgage Capital Markets; Inside
Mortgage Securities; Savings and Loan Fact Book.
for over 40 percent of the net increase; since 1989,
over 70 percent. This is nearly the entire con
ventional conforming loan market. The new
interpretation of the conforming loan limit allows
them to further increase their market share.
FHA and VA insure or guarantee a gradually
declining share of home mortgages, as Table 2
shows. It is not feasible to calculate noncon
forming loans as a fraction of the outstanding
stock of mortgages at any given time. The non
conforming market has been stable at about 20 to
22 percent of all conventional mortgages origi
nated in a given year, measured in terms of dollar
volume, but there has been a fairly steady
shrinkage when measured in terms of the number
of mortgages, from 11.6 percent in 1984 to 6.4 per
FEDERAL RESERVE BANK OF ST. LOUIS
cent in 1993. Even the stable dollar share of
annual originations implies a declining share
of all mortgages outstanding, as the conforming
loan limit rises from year to year.
The housing finance system is an emerging
duopoly, dominated by the two large GSEs.
Other institutions are increasingly limited to
segments of the market which are effectively
barred to the GSEs by statute, and which are
declining in importance.
The dominant position of the GSEs is rein
forced by their relationship to other market
institutions. Thrifts and banks are both their
competitors and their customers. They compete
as portfolio lenders, but at the same time they sell
53
Table 2
Government-Guaranteed and
Conventional Mortgages, 1968-92
1968
1980
1989
1992
51
34
94
102
180
265
770
965
283
157
1968
326
164
2464
2954
Dollar Values
(billions of current dollars)
FHA
VA
Conventional
Total
19.2
12.8
67.9
9.7
10.6
79.8
11.8
6.5
81.7
11.
5.
CO
00
Percent Shares
FHA
VA
Conventional
2408
Source: Dept, of Housing & Urban Development, Survey of
Mortgage Lending Activity.
mortgages to the GSEs and buy mortgage securities
from them, and also buy the debt securities that
the GSEs use to finance their portfolios.
THE TRADITIONAL SYSTEM:
A COMPARISON
This is very different from the housing finance
system as it existed about 25 years ago. In 1968 it
was still recognizably the New Deal system. It was
dominated by the S&Ls, which gathered deposits
locally, borrowed from the Home Loan Banks
during recessions or when rates were high, and
made long-term, fixed-rate loans (up to a maxi
mum of $40,000) on homes located within 50
miles of their home offices (100 miles after 1964).
The Federal Home Loan Bank Board (the Bank
Board) regulated and supervised both the S&Ls
and the Home Loan Banks, and insured the S&Ls
through the Federal Savings and Loan Insurance
Corporation (the FSLIC).
FHA was losing business to the S&Ls, and at
the same time taking on greater credit risk,
because of the growing private mortgage insur
ance industry. FHA had a single premium for
9 This paragraph is based on Kaserman (1977).
10 See Fredrikson (1971) and the data and literature therein
cited on changes in regional differentials. Actual average
mortgage rates varied by about 1 percentage point between
the Northeast at the low end and the South and West at the
high end, and may have risen slightly between 1940 and
1963. These rates are not risk-adjusted, but Fredrikson
makes adjustments for loan-to-value ratio and term, and
finds they have little effect on the regional differentials.
all loans; on the “principle of cross-subsidization,”
profits on the less risky loans were supposed to
subsidize losses on those with higher loan-to-value
ratios. The outcome was that FHA lost the better
loans to the conventional market, because private
mortgage insurers could charge a lower premium
on the less risky loans.9
The only secondary market agency was FNMA,
established in 1938 as a fully governmental
agency and limited to FHA and VA mortgages.
Its purpose was to smooth out the flow of mort
gage credit, over time and between places.
Securitization had not yet been invented; FNMA
issued bonds and bought mortgages from primary
lenders and mortgage bankers. It was supposed
to be a dealer, selling as well as buying mortgages.
It had begun to operate as a portfolio lender in
the post-war period, however, buying VA mort
gages in particular, until directed to liquidate its
portfolio by the 1954 FNMA Charter Act. Its
portfolio then fluctuated between $2 billion and
$3 billion until 1965. At that point it again
began to buy mortgages in large volume. Its
portfolio reached $7 billion in 1968, less than
3 percent of the total market.
This system was considered a success in terms
of its policy objectives. Housing production
reached unprecedented levels in the post-war
period; the pre-war peak of 937,000 housing
starts in 1925 was eclipsed in 1946 and indeed
in all later years. There was also a remarkable
increase in homeownership, from 44 percent of
all households in 1940 to 55 percent in 1950
and 62 percent by 1960. Total home mortgage
debt doubled in the first five years after the war
and doubled again in the next five years. Not all
the goals were met; regional differences in mort
gage rates probably did not diminish, but this
was a secondary concern.10 Contemporary econ
omists were divided over whether the housing
finance system was a major contributor to these
outcomes, or whether the same results could
have been reached some other way, but as a policy
matter the system was credited with the successes
that occurred.11
11 Grebler, Blank and Winnick (1956) argue that the changes in
the housing finance system were important; Saulnier,
Halcrow and Jacoby (1958) conclude they were not.
JULY/AUGUST 1994
54
Several problems were inherent in this system,
and by the late 1960s it was already starting to
break down. The S&Ls were expected to incur
interest rate risk routinely. They borrowed short
and they had to lend long. If interest rates rose,
their cost of funds would rise faster than the
earnings on their long-term mortgage portfolios.
Second, they operated under a kind of one-way
Glass-Steagall Act. They had no protection from
competition on either side of the balance sheet.
They could issue only time deposits and had to
specialize in home mortgages. Commercial
banks could, however, also issue time deposits
and make mortgage loans. Third, the geographic
lending restrictions meant that S&Ls incurred
credit risk from local as well as national eco
nomic changes. This had already occurred
on a large scale when the Florida land boom
collapsed in the late 1920s.12
CHANGES IN THE SYSTEM
All these potential problems became real
ones after 1965 and forced changes in the system.
The disintegration that began with the onset of
inflation in the late 1960s has been described
and analyzed by many economists.13 In this paper
only a brief review of the process of change is
necessary. Table 1 traces its course. It shows
the importance of different institutions in the
mortgage market in 1968, as the New Deal system
was starting to unravel: in 1980, when policy
makers were forced to recognize that the S&Ls
could no longer function as portfolio lenders in
an inflationary world; in 1989, when FIRREA
w as p assed to ad d ress the losses of the S&Ls and
the insolvency of the FSLIC; and in 1992, the
latest year for which information is available.
Inflation and the D ecline o f the S&Ls
The S&Ls remained the dominant institutions
in the mortgage market during the 1970s. They
held over 40 percent of all home mortgages in
12 Between 1927 and 1929, 40 percent of the S&Ls in Florida,
with almost half of the assets, went out of business, while
S&Ls in the rest of the country were expanding. See
Bodfish (1931) for these data.
13 For analyses of the problems of the S&Ls during the 1970s
and 1980s, see Barth (1991) and White (1991); White was a
member of the Federal Home Loan Bank Board and Barth
was chief economist there during the late 1980s. Jones
(1979) describes the policy process during the 1970s. The
most extensive analysis of the secondary market is U.S.
Department of Housing and Urban Development (1987).
Weicher (1988) describes the changes in the system as a
whole and the developing problems that led to the passage
of FIRREA.
Digitized for FEDERAL
FRASER RESERVE BANK OF ST. LOUIS
1980 as they did in 1968, and they accounted
for almost half of the net increase in mortgages
outstanding over the period. But this was
increasingly against their will. Once inflation
began to accelerate, they could not finance their
portfolios of fixed-rate long-term mortgages with
short-term deposits, unless depositors would
accept below-market rates. The small saver
proved unwilling to subsidize the homebuyer,
if alternative investments paying market rates
were available. Money market mutual funds
(MMMFs) were such an investment. Beginning
in 1972 the S&Ls’ cost of funds began to rise
relative to short-term Treasury rates.14 By 1980
the net income of the S&Ls as a whole was
approaching zero, tangible net worth was start
ing to fall, and the industry had a net worth in
market value terms variously calculated to be
between -8 and -19 percent of its assets.15
Major legislation was enacted in 1980 and
1982 that liberalized both the asset and liability
sides of S&L balance sheets. The goal of saving
them as institutions took precedence over the
goal of promoting housing. They were allowed
to make loans and direct investments outside of
housing altogether, up to 40 percent of their
assets. Between 1980 and 1989, they accounted
for less than a quarter of the increase in out
standing mortgages, and more than half of their
growth took the form of security purchases
rather than portfolio lending. By 1989 they held
only about 30 percent of outstanding mortgages
either in portfolio or as securities. Since the
passage of FIRREA, closure of failed S&Ls has
red u ced the total portfolio of the ind u stry by
over $175 billion, and their share of the market
is now under 20 percent.
The Evolution o f the
Secondary M arket
The dates in Table 1 also represent stages in
the evolution of the secondary market. Between
14 The Eleventh District Cost of Funds rose from 9 basis points
below the three-month Treasury rate in 1972 to 61 basis
points above it in 1987. (The Eleventh District Federal
Home Loan Bank is located in San Francisco and the district
includes the states of Arizona, California and Nevada. Its
Cost of Funds, measuring the interest rate on deposits paid
by S&Ls in the district, is one of the common indices for
ARMs.)
15 See, for example, Brewer (1989), Brumbaugh (1988) and
Kane (1985). Brewer’s estimate is the lowest, Kane’s the
highest. Brumbaugh’s is -12.5 percent.
55
1968 and 1980, the secondary market took on its
present institutional structure, securitization
was invented, and the first mortgage securities
won market acceptance.
Two legislative changes— one in 1954 requir
ing FNMA to buy mortgages on privately owned
low-income housing projects subsidized by the
government, and the other in 1967 treating the
purchases as a federal budget outlay—resulted
in splitting FNMA into two agencies in 1968
and changing its role.16 GNMA was created to
take responsibility for the low-income mort
gages, and FNMA went off-budget as a federally
chartered corporation with agency status in the
capital markets.
In 1970, amid concerns about rising interest
rates and a new “credit crunch” in the primary
mortgage market as a result of Reg Q, policymakers
responded by turning to the secondary market.
In the Emergency Home Finance Act of 1970,
FNMA was given authority to buy conventional
mortgages as well as those guaranteed or insured
by the federal government. At the same time,
the S&Ls acquired their own federally chartered
secondary market facility, the Federal Home
Loan Mortgage Corporation (FHLMC). FHLMC
was supposed to buy the S&Ls’ current conven
tional mortgage portfolios to “free up” funds for
new loans—in effect trying to shift the conse
quences of monetary policy to other sectors
of the economy. Like the Home Loan Banks,
FHLMC was wholly owned by the S&Ls.17
Thus, where there had been one secondary
market agency in 1967, there were three in 1970.
They had different ownership and they acted in
different ways.
GNMA operated as a secondary market agency
very much in the original intent of the New Deal
system. It did not buy and sell mortgages, but it
achieved the same result by issuing securities.
16 Under the 1967 federal budget reform, purchases of subsi
dized mortgages were raising outlays on a dollar-for-dollar
basis, even though part of the principal and interest on the
mortgage would be paid to the government by the borrower.
Subsequent budget reforms have changed this accounting
practice. Under current law, the entire principal amount of a
mortgage purchased or insured by the federal government is
counted in the credit budget, but only the anticipated subsidy
is included as a outlay in the administrative budget.
It created the first M BSs in 1970; by 1980 it was
securitizing virtually all new FHA and VA loans,
and its M BSs accounted for almost 10 percent of
all outstanding mortgages. FHLMC followed
GNMA into the securities business on a much
smaller scale and became primarily an issuer
of MBSs backed by conventional mortgages.
FNMA took a different route. During the 1970s,
it turned itself into the largest conventional
mortgage portfolio lender and thus, in effect, the
largest S&L in the country, albeit with different
sources of funds. Its experience paralleled that
of the S&Ls. It did not foresee the inflation of
the 1970s, so that its net worth also turned nega
tive in the late 1970s: its 1980 value of -16 per
cent was similar to the S&L industry.18
During the 1980s, securitization accounted
for over half the growth in the total volume
of mortgage credit. In 1981 both FNMA and
FHLMC initiated mortgage swap programs,
buying S&L portfolios and issuing pass-through
securities on exactly the same mortgages in return.
This brought FNMA into the business of issuing
securities, rather belatedly. Since then, both
its portfolio and its M BS volume have grown
rapidly. Its outstanding M BSs are now 3.5
times the size of its portfolio, but it remains
the largest portfolio lender. Besides issuing
pass-throughs to S&Ls, FHLMC created the
CMO in 1983 and expanded its securities
business almost twentyfold.
FIRREA marks a further stage in the evolution
of the secondary market. It turned FHLMC into
nearly a carbon copy of FNMA, giving it exactly
the same kind of board of directors and a very
similar charter. After FIRREA, the secondary
market institutions assumed a dominant position
in the mortgage market. Between 1968 and 1980,
about 80 percent of the net increase in mortgages
was held in portfolio and 20 percent was securi
tized; since 1989 the proportions have been
holdings of FHA and VA mortgages, and also that FNMA’s
debt issuances would drive up interest rates and raise the
cost of funds to the S&Ls and other primary mortgage
lenders. Burns raised the issue of illiquidity and expressed
concern that FHLMC would drive up interest rates on FHA
and VA mortgages. See U.S. Department of Housing and
Urban Development (1987).
18 U.S. Department of Housing and Urban Development
(1987), based on Kane and Foster (1986).
17 Opposition to allowing FNMA to buy conventional mortgages
was stated by Federal Reserve Chairman Martin in 1969
and opposition to creating FHLMC was stated by Federal
Reserve Chairman Burns in 1970. Martin expressed con
cern that FNMA’s conventional mortgage portfolio would be
illiquid and, therefore, might ultimately displace FNMA’s
JULY/AUGUST 1994
56
reversed. GSE portfolios also continued to grow
as a share of the market.
Did the System “Work” A fter 1965?
Housing advocates opposed many of the policy
changes for fear they would weaken the ability
of the system to allocate credit to housing,
regardless of the consequences for the financial
system or the economy. This was the key concern
preventing financial reform in the 1970s: If the
S&Ls were allowed to diversify, who would “fill
the gap” in the mortgage market? This concern
proved to be unfounded. The secondary market
agencies filled the gap, as Table 1 shows, and
the volume of outstanding mortgages almost
tripled between 1980 and 1989.
A second concern was the cost of mortgage credit.
This too has proved to be largely unfounded. The
spreads between mortgage and bond rates may
have widened during the 1970s and early 1980s,
but by the late 1980s the conventional mortgage
market may have become fully integrated with
the capital markets.19 Here also, the growing
role of the GSEs offset the declining presence of
the S&Ls, holding down the mortgage rate in the
conforming loan market.
Regional differences in mortgages rates probably
disappeared by the m id-1980s, as a result of
securitization and deregulation. Available data
on interregional flows of mortgage funds suggest
that securitization resulted in transfers from the
Northeast and Midwest to the South and West,
where population and housing demand were
growing, and, as already noted, in 1983 the S&Ls
were allowed to make mortgage loans anywhere
in the country.20 The developing S&L crisis in
the 1980s also helped create a national mortgage
market. One way in which the Bank Board
19 Hendershott and Van Order (1989) conclude that the interest
rate on conventional, fixed-rate mortgages rose by about
100 basis points between the late 1970s and the mid-1980s,
compared to the rate that would have prevailed in a perfect
market; then it fell by about 50 basis points between 1986
and 1988 to the market rate. Other studies covering a shorter
period and comparing the mortgage and bond rates also find
that the conventional mortgage rate began rising in relative
terms sometime in the 1970s, before deregulation of the S&Ls.
See, for example, Kaufman (1981), Tuccillo, Van Order and
Villani (1982) and Hendershott, Shilling and Villani (1983).
The Hendershott and Van Order study ends in 1988, and
there does not appear to be any more recent analysis of the
spread; given the year-to-year fluctuations in the spread
which they calculate, it would be desirable to see more
recent data before concluding that the actual conventional
conforming loan rate is the same as the rate in a perfectly
competitive market. Cotterman (1994) notes that the spread
between the MBS and Treasury rates fluctuated between
1984 and 1990, and was at its lowest level in 1988 and 1990.
Digitized for FEDERAL
FRASER RESERVE BANK OF ST. LOUIS
handled failing S&Ls was to sell them for their
franchise value to other S&Ls—at first in the same
market, then in the same state, then in other states,
as the number and severity of failures rose and
the financial resources of the FSLIC were
increasingly inadequate.
The system had less success in achieving its
other purposes. Since 1965 the homeownership
rate has fluctuated in a fairly narrow range,
between 62 and 66 percent of all households.21
There was a notable increase among young
families during the 1970s, but this was simply
a result of inflation. Young families bought
homes as soon as they could because owning
a home was the best inflation hedge available,
especially as inflation pushed them into higher
marginal tax brackets. In the 1980s disinflation
and reductions in marginal tax rates caused
their homeownership rate to drop quickly back
to its 1970 level.
Housing cycles, like economic cycles in general,
became more pronounced. Record years of over
2 m illion housing starts annually in 1971-73
were followed by a postwar low in 1975; another
year of 2 m illion in 1978 was followed by new
lows in 1981 and 1982. The housing finance
system could not have been expected to offset
completely the effects of the oil shocks and
other macroeconomic changes, but it is doubtful
if it achieved its stated more modest objective of
mitigating their impact on housing and shifting
part of the consequences to other sectors. The
S&Ls used advances from the Home Loan Banks
to offset deposit outflows, and this may have
had some effect. FNMA may also have mitigated
the cycles to a lesser extent through the late 1970s,
but it was not aggressively countercyclical, and it
may have had no effect in the recessions of 1980
20 Rudolph, Zumpano and Karson (1982) find that interregional
interest rate differences still existed in the mid-1970s, while
Karson, Rudolph and Zumpano (1986) conclude that they
did not exist by the mid-1980s. King and Andrukonis (1984)
report that FHLMC securities generated a gross transfer of
over $5 billion during their first decade. Information on net
interregional flows of mortgage funds is not available, but
the existence of substantial gross flows suggests that securi
tization played a significant role in eliminating regional rate
differentials.
21 The difference in the trend after 1960 may be partly attribut
able to demographic changes, especially the increasing pro
portion of households in categories in which homeownership
is less common, such as single individuals and single parents.
57
and 1981-82.22 FNMA’s purchases of conven
tional mortgages dropped by about one-third
from 1979 to 1981, which does not suggest that
it tried to act countercyclically.
Thus, even during this period of institutional
change and upheaval, the system continued to
allocate credit to housing, albeit at somewhat
higher mortgage rates, and a fully national mort
gage market developed. But cyclical fluctuations
in housing were severe and the homeownership
rate stopped rising, raising the question of whether
the system was still achieving its basic purpose.
POLICY ISSUES: SAFETY AND
SOUNDNESS VS. PUBLIC PURPOSE
The housing finance system continues to
evolve. Congress has enacted three major laws
in the last five years, affecting every institution
in the system, and may consider further legisla
tion for the Federal Home Loan Bank System.23
Some important provisions of these laws have
not yet been implemented; when they are, they
may in turn provoke further changes. The laws
have addressed two kinds of issues: policy mat
ters—what purposes the system w ill serve and
how it will achieve them; and regulatory mat
ters—what powers different institutions will
have and how they will be regulated.
In the policy area, all three new laws represent
a balancing of public purpose against “safety and
soundness,” the implicit objective that the system
not impose direct costs on taxpayers that must be
met by legislated appropriations. In the wake of
the S&Ls’ problems, there has been a much stronger
emphasis on safety and soundness; new capital
requirements have been imposed on most insti
tutions within the system. But there are elements
in each law that concern the public purposes, and
there is some evidence that the pendulum may be
swinging back toward a renewed emphasis on
22 See Grebler (1977) and Jaffee and Rosen (1979) for the
earlier cycles, and Kaufman (1985) for the 1980-82 reces
sions. Grebler analyzes both Home Loan Bank advances
and FNMA purchases.
23 The three laws are: FIRREA, concerning the S&Ls, the
Federal Home Loan Bank Board (which it abolished),
FHLMC, and to a lesser extent the Federal Home Loan
Banks; Title 5 of the National Affordable Housing Act of
1990, concerning FHA; and the Federal Housing Enterprises
Financial Safety and Soundness Act of 1992, enacted as
Title 13 of the Housing and Community Development Act of
1992, concerning FNMA and FHLMC. In addition, Congress
in 1992 required five separate studies of the Federal Home
Loan Bank System as the precursor to future legislation.
Four of these studies appeared during 1993, and the fifth in
April 1994. (The GSE legislation in 1992 was enacted after
these purposes. At the same time, some provi
sions of the new laws may make it more difficult
to achieve them.
Safety and Soundness
The new laws raise capital standards and
take account of risk differentials among assets
for virtually all institutions within the housing
finance system. FIRREA imposed more stringent
capital requirements on the S&Ls. They must have
1.5 percent tangible capital relative to assets and
must meet the same risk-based capital standards
as national banks. The tangible net worth of the
S&Ls as a whole was only 0.7 percent in 1989.
Both FHA and the GSEs are required to hold
more capital than they had when the laws were
passed. The existing standards were not raised
so much as they were changed conceptually.
FHA had no specific capital standard, beyond
the legislative requirement that it be actuarially
sound, which was undefined. FNMA’s capital
requirement, established in its Charter Act, was
calculated as a debt-to-capital ratio. This meant
that it was only required to hold capital against
its portfolio. Because it did not need to issue
debt to finance its MBSs, FNMA’s capital-to-asset
ratio (including MBSs) was 1.1 percent in 1990.
Prior to FIRREA, FHLMC had no statutory capital
requirement; the Bank Board determined it as a
policy matter. FIRREA gave FHLMC the same
debt-to-capital standard as FNMA. With its larger
proportion of M BSs, its capital-to-asset ratio was
0.8 percent in 1990. These are quite low levels
of capital; had the GSEs been required to meet
the risk-based capital standards set for the S&Ls
in FIRREA, FNMA would have needed 2.5 times
as much capital as it actually had in 1990, and
FHLMC more than three times as much.24
Both the FHA and GSE standards are established
by “stress tests.” In other words, the entity must
Congress required and received nine separate reports from
various federal government agencies.)
24 The calculations of these various capital ratios are reported
in U.S. Department of Housing and Urban Development
(1990a, 1990b). The published debt-to-capital ratios in the
reports include only stockholders’ equity; on that basis, the
ratios are 0.8 percent for FNMA and 0.6 percent for FHLMC.
Regulatory capital is defined in the Charter Acts to include
retained earnings and subordinated debt. Subordinated
debt is not counted as equity under Generally Accepted
Accounting Principles because it takes precedence during
bankruptcy over ownership interests. The subordinated debt
of the GSEs is due and payable in the event of bankruptcy
or insolvency, which appears to limit the government’s ability
to rely on it as capital.
JULY/AUGUST 1994
58
have enough capital to survive a recession, with
the amount determined in advance by econo
metric analysis. Both are risk-adjusted capital
standards; riskier loans are more likely to default
and more capital is required against them.
The FHA standard was set on the basis of an
actuarial study by Price Waterhouse during
1989-90. Price Waterhouse recommended that
FHA should at a minimum have a net worth of
1.25 percent against insurance in force, instead
of the then-current level of about 1.0 percent.
The purpose was to ensure that FHA would
have positive net worth in the event of a typical
post-war recession. This standard was enacted
in 1990, to be effective in 1992, with a higher
standard of 2.0 percent in the year 2000. To
reach these targets, the insurance premium was
raised by about 70 percent, in present value
terms, and risk-related premiums were estab
lished for the first time. Minimum equity
requirements for FHA homebuyers were also
raised, to reduce defaults and strengthen the
insurance fund; this increase, however, was
partly rolled back in 1992.25
The GSE stress test is based on their worst
actual regional experience, which for both has
been Texas in the mid-1980s. They are supposed
to have enough capital to withstand such a
recession if it occurred on the national level,
and also to survive large (600 basis points)
upward or downward changes in interest rates
occurring within a period of one year and lasting
for 10 years. Both mortgages held in portfolio
and M BSs are included.
The GSE capital standard includes more than
the stress test. It also defines two lower levels
of capital, in the form of ratios against mortgages
held in portfolio and MBSs. The authority of the
regulator varies depending on the GSE’s actual
capital relative to the levels defined in the statute.
The “minimum” capital level is 2.5 percent
against mortgages held in portfolio and 0.45 per
cent against M BSs, which matched FNMA’s
25 The 1990 legislation required FHA mortgagors to have at
least 2.25 percent equity in their home when they bought it
(1.25 percent for mortgages under $50,000). Previously, it
was possible to buy a home with no real equity, because
buyers were allowed to finance the closing costs in their
mortgage. On loans below $50,000, the minimum down
payment is 3 percent; on loans over $50,000, it is 3 percent
of the first $25,000 and 5 percent over $25,000. Closing
costs average 2 to 3 percent, ranging up to 6 percent in a
few states. The down payment in effect paid the closing
costs for a substantial number of FHA-insured homebuyers.
For analysis of the relationship between defaults and initial
FEDERAL RESERVE BANK OF ST. LOUIS
actual capital position as of 1991, and was slightly
more than FHLMC’s capital. (FHLMC was given
18 months to meet the minimum level without
incurring any regulatory sanctions, and it now
does.) The “critical” capital level is half of the
minimum level; if capital falls below it, the
regulator can immediately put the GSE into
receivership.
The GSEs’ risk-based capital standard is almost
certainly less stringent than the standard for
thrifts and banks, and the minimum standard
clearly is lower. Depository institutions must
have 4 percent capital against a mortgage in
their portfolio, while the GSEs must only have
2.5 percent. If a mortgage is securitized by the
GSEs and the security is held by a thrift or bank,
total capital is still less: 2.05 percent, consisting
of 1.6 percent for the depository institution to
protect against interest rate risk and 0.45 percent
for the GSE to protect against credit risk.
The FHA and GSE standards were established
in very different ways. In the case of FHA, an
econometric analysis was conducted and the
results were known before legislation was passed.
The law set new parameters for FHA insurance
partly on the basis of whether they would enable
FHA to achieve the standard. In the case of the
GSEs, the stress test is prescribed as much as
possible in the statute, but it was not performed
before the bill was passed. Instead, it was nego
tiated between the Bush Administration and the
GSEs and written into law by Congress without
analysis of how much capital w ill be required to
meet it. The test must be formally stated in reg
ulations by November 1994, and does not
become effective for another year.
Capital standards for the Federal Home Loan
Banks may be the subject of legislation in the
near future. Their capital now consists only of
the stock that S&Ls and other institutions have
had to buy in order to be members of the Home
Loan Bank System and to obtain advances.
Members can withdraw from the System and sell
loan-to-value ratios, showing a strong positive correlation,
see Price Waterhouse (1990) and Hendershott and Schultz
(1993), and the literature cited therein. For a more detailed
discussion of the 1990 FHA legislation, see Weicher (1992).
59
their stock back to their Home Loan Bank, subject
to an advance notice requirement of six months.
Thus, it is problematic whether the capital would
be available if individual Home Loan Banks began
to incur losses. The members have an incentive,
and a right, to withdraw their capital just when
it is most needed.
But the Home Loan Banks have so little capital
because of public policy. They had $2 billion in
retained earnings until FIRREA took that money
to cover part of the cost of S&L failures. FIRREA
also required them to contribute $300 m illion
per year out of their future earnings. That is
why the only capital they now have is the stock
owned by the members. It is going to be difficult
to build capital through new retained earnings.
Even if Congress were to repeal the $300 m illion
annual contribution, the S&Ls and probably the
newer members are likely to prefer having this
money passed through as dividends rather than
remaining as retained earnings, which could be
taken away again. In their studies of the Home
Loan Banks, both the General Accounting Office
and the Clinton Administration have argued that
they need more capital, but neither has offered a
specific proposal for raising it.
Countercyclical Support fo r
Housing Construction
The emphasis on safety and soundness creates
a clear potential conflict with the traditional
countercyclical objective of the housing finance
system. This is most obvious with respect to the
GSEs, where it was explicitly discussed in eval
uating the adequacy of their present capital. In
its annual reports as regulator of FNMA and
FHLMC prior to legislative consideration of a
new capital standard, HUD used a Depression
scenario to assess capital adequacy, based on
one used by Moody’s to rate private mortgage
insurers. HUD concluded that neither GSE could
survive 10 years of the Depression scenario, but
26 These results are for 1991, as reported in U.S. Department
of Housing and Urban Development (1992a, 1992b). Similar
tests for 1990 show that FHLMC could survive six years and
FNMA seven (U.S. Department of Housing and Urban
Development, 1991b). The 1991 test is more detailed and
sophisticated. The test is stringent: It includes a 10 percent
decline in house prices for four straight years, for example.
It is necessary to survive 10 years of the Moody’s
Depression scenario to qualify for an AAA rating; very few
financial institutions are rated AAA. The HUD stress test is
not identical to the Moody’s scenario, although it is closely
modeled on the scenario. Thus, it cannot be said that the
GSEs would or would not receive an AAA rating from
Moody’s, or conversely that any other financial institution
would or would not survive 10 years of the HUD stress test.
both could last six years.26 This analysis
assumed that they continued to be active in the
mortgage market during the Depression to the
same extent as previously; FNMA and FHLMC
could survive a full 10 years of the Depression
scenario, if they immediately suspended opera
tions at the beginning of the Depression. In
response, the GSEs stated that they would in
fact cease buying mortgages immediately.27
This, of course, raises the question of whether
they could recognize the onset of a depression
immediately (a delay of two years would be
enough to cut the period of survival from 10 to
six years for both GSEs). The 1992 legislation
accepted the GSE position on at least an interim
basis. The stress test must assume that the GSEs
accept no new business until the General
Accounting Office and Congressional Budget
Office complete studies of the appropriate new
business assumptions. The studies are due in
November 1995. The GSEs have also said they
would increase their guarantee fees if necessary
to remain solvent, but it is not easy to raise
prices during a recession.
It should be possible for a GSE to buy mortgages
in periods of high interest rates, earn a profit if
rates decline, and perhaps moderate fluctuations
in housing production in the process. The
opportunity to profit from interest rate declines
is limited, but not eliminated, by the prepayment
option. On the other hand, countercyclical
behavior may result in credit risk. If the quality
distribution of loans offered in a recession is the
same as during an expansion, then it is necessary
to buy lower quality mortgages in order to be
actively countercyclical.
The potential conflict has been discussed in
every downturn. The legislative changes probably
heighten it. The GSEs still have Charter Act
responsibilities to “provide ongoing support to
the mortgage market,” but a capital standard that
assumes they do not.
An AAA rating is not likely, however. In 1991 Standard and
Poor’s evaluated both GSEs at the request of the Treasury,
rating FHLMC as A+ and FNMA as A- on the assumption that
the GSEs did not have agency status, which in fact they do.
27 The reaction of the GSEs appears in U.S. Department of
Housing and Urban Development (1991b).
JULY/AUGUST 1994
60
At present these issues are hypothetical, but
in a severe downturn they would become real.
They would then attract policymakers’ attention
and perhaps result in further changes.
“U nderserved” A reas and Groups
The traditional goal of making mortgage credit
equally available across the country has taken
new forms in FIRREA and the GSE legislation.
The focus of concern has shifted from regions to
communities, particularly low-income urban
neighborhoods and those with predominantly
minority residents, and also to individuals.
Explicit subsidies through the housing finance
system are being provided and proposed to meet
this goal. FIRREA required the Home Loan
Banks to subsidize low-income housing directly
by allocating 20 percent of their profits to a new
Affordable Housing Program, with a minimum
annual amount starting at $50 m illion and
increasing to $100 m illion by 1995. This is
essentially another tax on the Home Loan Banks
and through them the S&Ls. The Clinton
Administration’s report on the Home Loan Bank
System goes farther and proposes a specific
mandate to facilitate mortgage lending to lowerincome families and targeted populations. This
would be a new role for the Home Loan Banks.
Support for low- and moderate-income housing
has been one of the purposes of FNMA and
FHLMC, as stated in their Charter Acts.28 This
became the major Congressional concern in
1992, once the Administration and the GSEs
agreed on a capital standard. The law sets two
general goals that certain percentages (to be
determined by the HUD Secretary) should be for
units occupied by families with incomes below
median, and for housing in central cities. Both
goals include rental housing as well as homes.29
The law allows a number of acceptable reasons
for not meeting any goal in a given year, and a
multi-year regulatory process before any sanc
tions could be imposed for falling short.
28 Both GSEs are required “to provide ongoing assistance to
the secondary market for residential mortgages (including
activities relating to mortgages on housing for low- and
moderate-income families involving a reasonable economic
return that may be less than the return earned on other
activities)...” See 12 U.S.C. § 1716.
29 The law also sets a special affordable housing goal that
1 percent of each GSE’s purchases should be for housing
affordable to low-income families or located in low-income
neighborhoods, with allocated shares for single-family and
multifamily housing.
FEDERAL RESERVE BANK OF ST. LOUIS
The law also sets transition goals. Each GSE
is to have at least 30 percent of its purchases for
housing occupied by families below median
income by 1994, rising in two steps from their
1992 levels. This is about the share of the con
ventional conforming loan market consisting of
buyers in this income range. The GSEs have not
come very close to this percentage in the past for
single-family houses; both were below 25 percent
in 1991. Nearly all apartments, however, are
affordable by families of median income by the
rules of thumb set forth in the legislation. Both
GSEs met the 1993 targets established by HUD.
Similar transition goals were established for
central cities, and in this case neither GSE met
the 1993 goal. Under HUD’s regulations they
are now required to file housing plans to describe
how they will meet them in the future.
These housing goals pose another potential
conflict between the safety and soundness of the
housing finance system (and also the financial
interests of the private and quasi-private housing
finance institutions) and a public purpose which
is becoming increasingly prominent. Both the
GSEs and the Home Loan Banks have pointed
out the conflict. The issue is more serious for
the Home Loan Banks because they must fund
the Affordable Housing Program. This require
ment, like the $300 m illion contribution to the
cost of S&L resolutions, has been used by the
Home Loan Banks to justify making investments
with the funds that they borrow on the capital
markets as the demand for advances has fallen,
and thus perhaps to undertake new types of risk.
FNMA and FHLMC are required only to buy
loans for moderate-income housing, not to pro
vide subsidies, and they need not lower their
underwriting standards. The general conclusion
of the mortgage default literature is that default
is largely a function of the loan-to-value ratio on
the mortgage and not closely related to either
the value of a home or the income of the buyer.30
But even if moderate-income housing turned out
30 See Hendershott and Schultz (1993) and the literature cited
therein. Hendershott and Schultz do find that foreclosures
on FHA-insured loans are inversely related to loan size,
which they attribute to differential underwriting standards or
house price appreciation rates. The latter explanation might
indicate greater risk for small loans.
61
to be riskier, it would be possible for the GSEs to
take more risk than the S&Ls, given their lower
cost of funds. The charter acts and the legislation
seem to expect that the GSEs will use their agency
status to make loans to moderate-income buyers,
without jeopardizing their safety and soundness.
The Administration’s proposed lower-income
mandate for the Home Loan Banks takes a similar
view, stating that collateral requirements should
not be relaxed to meet the mandate.
REGULATORY ISSUES
The Structure o f Regulation
At the same time that capital standards were
being raised for most entities within the system,
all of the private institutions were given new
regulators. The Bank Board was abolished and
its duties parcelled out among several agencies.
Some of the potential conflicts between public
purpose and safety and soundness are reflected
in the new regulatory structure. The 1992 GSE
legislation divided authority between the Secretary
of HUD and the Director of a new Office of
Federal Housing Enterprise Oversight (OFHEO),
which is formally part of HUD but is effectively
independent of the Secretary. The Director reg
ulates for safety and soundness; the Secretary
establishes, monitors, and enforces the housing
goals and regulates the GSEs in all areas other
than safety and soundness. For example, the
Secretary rather than the Director approves new
programs, and the Secretary rather than the
Director raised the issue of whether the GSEs
had to reduce their maximum mortgage amount
when the conforming loan limit declined last
year. The effectiveness of this relationship has
not yet been tested, since the Office is still in the
formative stage and has not yet had to issue any
of the regulations required by the law.
Both the GAO and the Administration studies
of the Home Loan Banks have recommended
31 White (1991) favors deregulation, but says it came 15 years
too late and should have been accompanied by stronger
safety and soundness regulation, and by risk-adjusted
deposit insurance premiums. He reviews the literature
showing that losses were positively related to use of the new
powers. Barth (1991) favors deregulation but says that it
contributed to the problems of some S&Ls. Kane (1989)
argues that deregulation did not cause the problems of S&Ls
and re-regulation would not solve them, but goes on to say
that deregulation expanded opportunities for poorly man
aged S&ls to fail, as well as allowing well-managed ones to
rebuild their net worth. Rudolph (1989) analyzed the subse
quent behavior of S&Ls that were insolvent in 1982 and
found that traditional housing lenders were more likely to be
that they be regulated by OFHEO. At present
they are regulated by the Federal Housing
Finance Board, created in FIRREA as an after
thought for that sole purpose. The ostensible
reason for abolishing the Bank Board was that it
acted as an advocate for the industry it was sup
posed to regulate. The risk that the regulated
entities would capture the regulator would seem
to be still greater for the Federal Housing
Finance Board, with nothing to do but regulate
the 12 Home Loan Banks, and for OFHEO, regu
lating only the two GSEs. It is probably prefer
able to have one regulator for all 14 institutions,
rather than two, although FNMA and FHLMC do
not favor sharing their regulator. Whether that
proposal is adopted, it seems likely that the reg
ulatory structure of the system will be revised
again.
Is T here A Future fo r Specialized
Portfolio Lenders?
Public policy has wrestled for two decades
with the question of whether specialized mort
gage portfolio lenders can exist. In the 1970s
policymakers decided they could and tried to
keep the S&Ls operating as they always had in
the face of inflation and new competition. In
the 1980s policy reversed itself, and S&Ls were
given broad new asset powers. In the 1990s
policy has reversed itself again. FIRREA adopted
the premise that deregulation caused the S&L
failures, a view not shared by most economists.31
It explicitly took away some of the powers granted
in 1980-82 and required S&Ls to put a higher
percentage of their assets in mortgages and
housing investments to keep their tax advantages,
although the latter restriction was somewhat
relaxed in 1991.32 S&Ls are not forced to be spe
cialized housing portfolio lenders, however; the
new capital rules give them an incentive to
move away from portfolio lending by requiring
only 40 percent as much capital against MBSs
issued by the GSEs as against whole mortgages.
insolvent in 1982-83, but less likely in 1986, which suggests
that among insolvent S&Ls, at least, those taking advantage
of the new powers were less successful than those which
“stayed in housing.”
32 White (1991) notes, however, that at the same time these
provisions were enacted, many members of Congress were
saying that S&Ls should be more like commercial banks.
JULY/AUGUST 1994
62
Meanwhile, the GSEs are thriving in part
because they are specialized lenders—very large
S&Ls, in that sense— as well as secondary market
agencies. Their portfolio operations are quite
profitable: Almost three-quarters of FNMA’s
revenue, and almost half of FHLMC’s, came
from their portfolios in 1992. FHLMC has recog
nized this since FIRREA gave it the same powers
and incentives as FNMA; it is behaving similarly,
expanding its portfolio by 70 percent and an
nouncing a business objective of further rapid
growth. FHLMC was already the fourth largest
portfolio lender in the United States, although
its portfolio always has been small relative to its
securities volume. The specialized portfolio
lender is alive and functioning to a greater
extent than is generally recognized.
Several factors contribute to the GSEs’ success
as portfolio lenders. A number of recent studies
conclude that the 20 to 35 basis point difference
between the conforming market and the jumbo
market is the margin between profit and loss for
S&Ls, on average. The cost advantage of the
GSEs is attributed to the lower capital require
ments they face, the tax exemptions and smaller
regulatory burdens granted them by their federal
charters, the fact that they do not have to pay
deposit insurance premiums or help to fund the
resolution of failed S&Ls, and economies of scale.33
The first two factors are benefits conferred
explicitly by act of Congress.
Macroeconomic conditions may also con
tribute to the GSEs’ recent success. If inflation
is erratic and unanticipated, it is probably not
possible to survive as a specialized portfolio
lender, as FNMA and the S&Ls showed during
the 1970s and early 1980s. If inflation is low
and stable, it is apparently still possible to be a
specialized portfolio lender, as the same institu
tions showed when inflation receded after 1982
and both FNMA and a large number of S&Ls
became profitable once again. FNMA especially
was saved by disinflation. It gambled on a
decline in interest rates (there was not much to
lose from such a gamble, from the stockholders’
point of view), buying mortgages in large vol
ume, and it benefitted greatly when rates fell.
Its net worth became positive in 1985. It has
tried to prevent a similar problem in the future.
A HUD analysis in 1991 concluded that it has
33 See Cotterman (1994) and McNulty and Pearce (1994) for
discussions of the literature. Goodman and Passmore (1992)
calculate that the difference in capital requirements alone
lowers the GSEs’ costs by about 35 basis points.
FEDERAL RESERVE BANK OF ST. LOUIS
effectively hedged against interest rate risk by
changing the duration of its liabilities, even
though most of its portfolio consists of fixed-rate
mortgages.
It is doubtful if S&Ls could do the same thing,
given their higher costs. They may be able to
prosper as portfolio lenders specializing to some
extent in fixed-rate mortgages by accepting inter
est rate risk, if inflation remains low and if the
yield curve remains upward sloping. They may
also survive as ARM lenders.
The broader geographic authority of the GSEs
may have been important in the 1980s. S&L fail
ures since deregulation have been concentrated
in states which suffered severe recessions,
notably Texas but also other energy and farm
states. The decline in domestic crude oil prices
between 1982 and 1989 precipitated a regional
recession in which commercial real estate val
ues in the Southwest fell by one-third. (Over
the same period, they rose nationally by about
10 percent.) Defaults on home mortgages and
other real estate rose rapidly. The geographic
restrictions on S&L portfolios meant that the bad
investments and loans were held in the portfo
lios of institutions in those states. One-fifth of
the S&Ls which failed during the 1980s were
located in Texas and they accounted for half of
the losses. Deposit insurance turned the region
al failures into a national problem.
It is now possible for an S&L, like a GSE, to
make or buy loans anywhere in the country.
This may be significant. Both FNMA and FHA
survived the Texas recession and other regional
problems during the mid-1980s. Both sustained
losses, but neither was driven to a negative net
worth position. Their experience suggests that
national portfolio lenders—in effect, national
S&Ls—could be viable. But the cost advantages
of the GSEs would remain.
GSE Powers
The competitive advantages conferred on the
GSEs by agency status raise the question of their
role as potential competitors in markets beyond
their current activities. This has been a recurring
issue for FNMA since it was privatized, when the
Secretary of HUD was given new program approval
authority. It has become an issue for FHLMC
63
since FIRREA. Typically, FNMA has sought
legislative authority from Congress if the Secretary
has denied or deferred approval. Usually, but
not always, Congress has given approval.
The most contentious instance is REMICs. The
Tax Reform Act of 1986 created these securities
and authorized FNMA and FHLMC to issue
REMICs backed by conventional mortgages,
subject to the approval of their regulators.34
Both agencies sought approval, over the strong
objections of Wall Street securities issuers, who
argued that they could enter this market if the
agencies did not, but could not compete with
them. The Federal Home Loan Bank Board
originally decided not to allow FHLMC to issue
REMICs, but HUD (under pressure from
Congress) eventually allowed FNMA to issue
them on a temporary basis, which became per
manent in 1988, and FHLMC was allowed to
issue them in 1988.
FNMA has also sought to move beyond mortgage
purchase and securitization, with less success.
In 1985 it proposed to buy bonds collateralized
by mortgages that would be issued by financing
subsidiaries of financial institutions. In 1990 it
requested approval of a program to buy debt
obligations secured by conventional mortgages,
or securities backed by such mortgages. The
former proposal brought objections from invest
ment bankers and the Senate Banking Committee
chairman and ranking minority member, as being
financing transactions rather than mortgage pur
chases, and HUD did not approve it. The latter
would have placed FNMA in competition with
the Home Loan Banks by letting it issue advances
against mortgage collateral, and HUD again
denied approval.35
34 REMICs have tax advantages over CMOs and were expected
to be a major innovation in mortgage securities.
35 HUD also denied approval on grounds that the program
involved significant risks to all parties, including the federal
government, and could adversely affect FNMA’s safety and
soundness since it could affect FNMA’s needs for capital.
The transactions would have allowed financial institutions
to defer recognition of economic losses and encourage
leveraging, possibly increasing the risk of bankruptcy by
the institution. Denial of new programs on safety and
soundness grounds has been relatively infrequent.
FNMA has also undertaken or considered
activities that are ancillary to its secondary market
operations but that are already provided by private
firms. In the m id-1980s, it raised the possibility
of establishing a mortgage insurance subsidiary,
in competition with the private mortgage insur
ance industry. In 1985 it acquired a computer
software firm with the intent of producing and
selling a loan origination and servicing program.36
The GSEs have strongly opposed any regulatory
limitation on their powers. This was a major issue
in the 1992 legislation. Ultimately, the HUD
Secretary retained the authority to deny approval
for a new program if he or she determines that
the program is “not in the public interest,” but
the Secretary has to act within 45 days, and the
law prescribes an appeals process which is
heavily weighted toward the GSEs. The law
also gives the GSEs broad authority to buy any
kind of home mortgage, limiting the Secretary’s
regulatory discretion.37 There is no reason to
think that the GSEs will not attempt to extend
their activities in the future, so the demarcation
of authority between different institutions will
probably continue to be a recurring issue.
CONCLUSION
One public policy issue which appears to be
resolved is the desirability of a housing finance
system to allocate credit to housing. This is a
change from recent years. For about a decade
beginning in the late 1970s, there was extensive
public discussion about dismantling the system
on the grounds that it was becoming too expen
sive for society to continue allocating credit to
housing, in two senses. Household investment
in housing was growing rapidly in response to
time, virtually the only conventional mortgages issued were
standard mortgages. As new instruments were developed
in the 1980s, FNMA claimed the authority to buy any kind
of conventional first mortgage under the “Romney letter,”
such as ARMs and balloon mortgages with different risk
characteristics than the standard mortgage. Proposed HUD
regulations issued in 1990 would have revoked this broad
interpretation. FNMA objected to the regulations, and they
were superseded by the 1992 legislation.
36 The regulatory issues raised by new activities between 1980
and 1985 are described in U.S. Department of Housing and
Urban Development (1987), the proposal to purchase debt
obligations secured by conventional mortgages in U.S.
Department of Housing and Urban Development (1991a).
37 In 1970 FNMA sought and received regulatory approval from
Secretary George Romney to begin a program of buying
conventional first mortgages on single-family homes. At the
JULY/AUGUST 1994
64
inflation in the late 1970s, with concomitant
underinvestment in productive capacity, and the
growing problems of the S&Ls were threatening
to impose direct costs on taxpayers.
Cotterman, Robert F. “The Effects of FHLMC’s and FNMA’s
Mortgage Activities,” in U.S. Department of Housing and
Urban Development, Report to Congress on the Federal
Home Loan Bank System, vol. 2: Analytical Studies. U.S.
Department of Housing and Urban Development, 1994.
A number of proposals were offered to address
these concerns. The Financial Reform Act con
sidered by the House of Representatives in 1976
would have turned the S&Ls into commercial
banks. The Reagan Administration offered budget
proposals to levy fees on the GSEs, which could
have been set at a level to cover the market value
of agency status. There were several studies of
privatizing one or both of them in the mid-1980s.
Fredrikson, E. Bruce. ‘The Geographic Structure of Residential
Mortgage Yields,” in Jack M. Guttentag, ed., Essays on
Interest Rates, vol. II. Columbia University Press, 1971.
But interest has faded since then. During con
sideration of FHA reform, no one (including its
competitors) made any suggestion to close FHA
down or turn it over to the private sector. Most
importantly, there was no real interest in priva
tizing either GSE in the extended process of
writing the 1992 legislation. The closest thing
to it was an amendment offered by Rep. Jim
Leach (R.-Iowa) on the floor of the House of
Representatives, which would have set higher
capital standards and eliminated some of the
GSEs’ privileges. The amendment lost on a
298-119 vote. No comparable proposal was
mentioned in the Senate.
Five years after FIRREA and 15 years after
public recognition that the New Deal housing
finance system was no longer viable, the United
States has a very different system. But the new
system still has the same purposes as the old one,
broadly speaking, and if anything the inherent
conflicts b etw een the p u rp oses of th e system
and the safety and soundness of the individual
institutions in it are more sharply drawn. While
the spectacular problems of the S&Ls have attracted
most of the recent attention, their role has sharply
diminished, and the important issues in the
future are likely to involve the GSEs.
REFERENCES
Barth, James R. The Great Savings and Loan Debacle.
American Enterprise Institute, 1991.
Bodfish, Morton. History of Building and Loan in the United
States. United States Building and Loan League, 1931.
Brewer, Elijah, III. “Full-Blown Crisis, Half-Measure Cure,”
Economic Perspectives (November/December 1989), pp. 2-17.
Brumbaugh, R. Dan, Jr. Thrifts Under Siege: Restoring Order
to American Banking. Ballinger, 1988.
FEDERAL RESERVE BANK OF ST. LOUIS
Goodman, John L., Jr., and S. Wayne Passmore. “Market
Power and the Pricing of Mortgage Securitization.” Federal
Reserve Board Finance and Economics Discussion Paper
No. 197 (March 1992).
Grebler, Leo. “An Assessment of the Performance of the Public
Sector in the Residential Housing Market: 1955-1974,” in
Robert M. Buckley, John A. Tuccillo, and Kevin E. Villani, eds.,
Capital Markets and the Housing Sector. Ballinger, 1977.
_____ , David M. Blank, and Louis Winnick. Capital Formation
in Residential Real Estate. Princeton University Press, 1956.
Hendershott, Patric H., and William R. Schultz. “Equity and
Nonequity Determinants of FHA Single-Family Mortgage
Foreclosures in the 1980s.” Journal o f the American Real
Estate and Urban Economics Association (winter 1993),
pp. 405-30.
_____ , and James D. Shilling. ‘The Impact of the Agencies on
Conventional Fixed-Rate Mortgage Yields,” Journal o f Real
Estate Finance and Economics (June, 1989), pp. 101-15.
_____ , _____ , and Kevin E. Villani. “Measurement of the
Spreads between Yields on Various Mortgage Contracts and
Treasury Securities,” AREUEA Journal (winter 1983), pp.
476-89.
_____ , and Robert Van Order. “Integration of Mortgage and
Capital Markets and the Accumulation of Residential
Capital,” Reqional Science & Urban Economics (May 1989),
pp. 189-210.
ICF, Incorporated. Effects of the Conforming Loan Limit on
Mortgage Markets. U.S. Department of Housing and Urban
Development, March 1990.
Jaffee, Dwight M., and Kenneth T. Rosen. “Mortgage Credit
Availability and Residential Construction," Brookings Papers
on Economic Activity (1979, No. 2), pp. 333-76.
Jones, Sidney L. The Development of Economic Policy:
Financial Institution Reform. Graduate School of Business
Administration, University of Michigan, 1979.
Kane, Edward J. The Gathering Crisis in Federal Deposit
Insurance. MIT Press, 1985.
_____ . ‘The Looting of FSLIC: What Went Wrong?” Ohio
State University College of Business Working Paper 89-3
(January 1989).
_____ , and Chester Foster. “Valuing and Eliminating
Subsidies Associated With Conjectural Government
Guarantees of FNMA Liabilities,” College of Administrative
Sciences Working Paper 86-71, Ohio State University (1986).
Karson, Marvin J., Patricia M. Rudolph, and Leonard V.
Zumpano. “Inter-Regional Differences in Conventional
Mortgage Terms: A Test of the Efficiency of the Residential
Mortgage Market,” paper presented at the American Real
Estate and Urban Economics Association, 1986.
65
Kaserman, David L. “An Econometric Analysis of the Decline in
Federal Mortgage Default Insurance,” in Robert M. Buckley,
John A. Tuccillo, and Kevin E. Villani, eds., Capital Markets
and the Housing Sector. Ballinger, 1977.
Kaufman, George. “Impact of Deregulation on the Mortgage
Market,” in Housing Finance in the Eighties: Issues and
Options. Federal National Mortgage Association, 1981.
Kaufman, Herbert. “FNMA and the Housing Cycle: Its Recent
Contribution and Its Future Role in a Deregulated
Environment,” in U.S. General Accounting Office, The
Federal National Mortgage Association in a Changing
Economic Environment. U.S. General Accounting Office, 1985.
King, A. Thomas, and David Andrukonis. “Who Holds PCs?”
Secondary Mortgage Markets (February 1984), pp. 12-17.
McNulty, James E., and James Pearce. “An Economic
Evaluation of Specialized Housing Lenders and the Qualified
Thrift Lender Test: A Review of the Literature,” in U.S.
Department of Housing and Urban Development, Report to
Congress on the Federal Home Loan Bank System, vol. 2:
Analytical Studies. U.S. Department of Housing and Urban
Development, 1994.
Morton, J.E. Urban Mortgage Lending: Comparative Markets
and Experience. Princeton University Press, 1956.
Price Waterhouse. An Actuarial Review o f the Federal Housing
Administration’s Mutual Mortgage Insurance Fund. Price
Waterhouse, 1990.
Rudolph, Patricia M. “The Insolvent Thrifts of 1982: Where Are
They Now?” AREUEA Journal (winter 1989), pp. 450-62.
_____ , Leonard V. Zumpano, and Marvin J. Karson. “Mortgage
Markets and Inter-Regional Differences in Conventional
Mortgage Terms,” AREUEA Journal (spring 1982), pp. 94110 .
Saulnier, R.J., Harold G. Halcrow and Neil H. Jacoby. Federal
Lending and Loan Insurance. Princeton University Press,
1958.
Tuccillo, John A., Robert Van Order, and Kevin E. Villani.
“Homeownership Policies and Mortgage Markets, 1960 to
1980,” Housing Finance Review (January 1982), pp. 1-21.
U.S. Department of Housing and Urban Development. 1991
Report to Congress on the Federal Home Loan Mortgage
Corporation. HUD, 1992a.
_____ . 1991 Report to Congress on the Federal National
Mortgage Association. HUD, 1992b.
_____ . 1990 Report to Congress on the Federal National
Mortgage Association. HUD, 1991a.
_____ . Capitalization Study o f the Federal National Mortgage
Association and the Federal Home Loan Mortgage
Corporation. HUD, 1991b.
_____ . 1989 Report to Congress on the Federal Home Loan
Mortgage Corporation. HUD, 1990a.
_____ . 1988-89 Report to Congress on the Federal National
Mortgage Association. HUD, 1990b.
_____ . 1986 Report to Congress on the Federal National
Mortgage Association. HUD, 1987.
U.S. General Accounting Office. Federal Home Loan Bank
System: Reforms Needed to Promote Its Safety,
Soundness, and Effectiveness. U.S. General Accounting
Office, GAO/GGD-94-38, December 1993.
Weicher, John C. “The Future Structure of the Housing
Finance System,” in William S. Haraf and Rose Marie
Kushmeider, eds., Restructuring Banking and Financial
Services in America. American Enterprise Institute, 1988.
_____ . “FHA Reform: Balancing Public Purpose and Financial
Soundness,” Journal of Real Estate Finance and Economics
(March 1992), pp. 133-50.
White, Lawrence J. The S & L Debacle. Oxford University
Press, 1991.
JULY/AUGUST 1994
Alvin L. Marty
Alvin L. Marty is professor of economics and finance at the
Center for Business and Government, Baruch College, City
University o f New York. The author is indebted to Philip
Cagan, Barry Ma and John Tatom for helpful comments and
suggestions. Li Li provided research assistance. The paper
was written while the author was a visiting scholar at the
Federal Reserve Bank of St. Louis.
The Inflation Tax and the
Marginal Welfare Cost in a
World of Currency and Deposits
H ow
HIGH IS THE OPTIMAL rate of inflation? The answer depends on the range of
benefits and costs associated with inflation that
are considered by the monetary authority in
choosing the inflation rate. For example, if one
considers the effects of inflation on the distribu
tions of income and wealth, its interactions with
the tax code or the transition cost of changing
the expected rate of inflation, or if one adopts
the alternative perspectives of different economic
agents, the benefits and costs can be relatively
large and difficult to assess. This article abstracts
from transitory and largely avoidable aspects of
inflation, and focuses instead on the fundamental
public finance aspects of the monetary authority’s
problem. In this case, the net benefits and costs
are those associated with an inflation rate that is
perfectly anticipated; the benefit of inflation that
accrues to the monetary authority (typically the
government) is the revenue from inflationary
money creation. This benefit is analogous to the
revenue arising from a specific tax on any other
good or service.
Inflation imposes a tax on money holdings
because it is the rate at which individuals lose
the purchasing power of a dollar. To lower the
total cost of holding money, individuals change
their holdings and their use of money when
inflation rises. Their efforts to do so, however,
reduce their total services from real money
balances, thereby lowering individuals’ real
income. This loss is the welfare cost of inflation.
The optimal rate of inflation is found by com
paring the marginal welfare cost of revenue from
inflation with the marginal cost of alternative
sources of revenue. An efficient system of tax
collection minimizes the welfare cost of a given
flow of tax revenue; this requires that the inflation
rate must be chosen so that the marginal cost per
dollar of revenue from inflation is the same as the
marginal cost of alternative sources of revenue.
In the analysis below, these concepts are devel
oped for models involving a money stock made
up of currency only, competitively priced bank
deposits only, and a mix of both. The differences
in each case clarify the analysis as well as provide
some insight into the implications of the analysis
for the optimal inflation rate.
THE MARGINAL WELFARE COST OF
REVENUE FROM MONEY CREATION:
THE CURRENCY CASE
Almost two decades ago, it was shown that a
simple formula provides a method of calculating
the additional welfare cost of collecting a dollar
of revenue from money creation. This measure
is the ratio of the marginal welfare cost of inflation
JULY/AUGUST 1994
68
to the marginal revenue from a change in antici
pated inflation.1 To derive this formula, assume
the only money is currency and that the demand
for real money balances depends only on the
nominal rate of interest, holding other influ
ences constant:
(1) m = (p[i)
The welfare loss, W, is
(2) W = j(p (x )d x - i(p{i)
and the marginal welfare loss from a rise in
inflation, n, is reflected in the incremental loss
from a rise in the nominal interest rate:
(3)
dW
di
Using the Phelps-Auernheimer (Phelps, 1973;
Auernheimer, 1974) definition of the revenue, R,
we have
(4) R = (p{i)i,
and the marginal revenue is
r/R
(5) — = (pU) + i(p'[i)-
di
Since the elasticity of demand for real balances is
(6) JV; = -
(p[i) ’
the marginal welfare cost per unit of revenue,
the ratio of equations 3 and 5, is
(7)
dW
dR
1 - N,
Equation 7 is a variant of the well-known Ramsey
tax rule (tax more heavily goods in inelastic
demand) and assumes, as does the Ramsey rule,
cross effects absent within the taxed sector. The
formula is useful in answering the question: What
rate of inflation (money rate of interest) would
equalize the marginal welfare cost per dollar
revenue accruing to inflation tax with an index
of such costs due to other distortionary taxes?
The analysis we are conducting is in the realm
of balanced budget incidence. We raise the
inflation tax on real balances until the marginal
1 The real rate of interest is held constant as the money rate
of interest, /, varies in such an analysis (Marty, 1976).
FEDERAL RESERVE BANK OF ST. LOUIS
welfare cost per dollar of revenue is equal to an
index of these per dollar distortions for other
taxes. The increase in revenue is used by the
government for exhaustive expenditures rather
than rebated to consumers directly, or indirectly
through reduced taxes.
Another observation is in order. Although I
have illustrated the use of these formulas by
plugging in estimates of the marginal welfare
cost, the main contribution of the paper lies in
the provision of the formulas themselves. If
these formulas pass muster, other empirical
observations can be plugged in.
Assume the demand for real cash balances fol
lows the Cagan semi-log form M/P = A exp(-bi).
Friedman (1971) uses three alternative values
of b, 5, 10 or 20. Laidler (1986) cites .15 as the
typical interest elasticity of demand for M l. If
we assume the real rate is 1.5 percent, which
equals the money rate at zero inflation, the value
of b is .15/.015 or 10 percent. To err on the side
of charity to inflationary finance, we use a value
of 5 for b. Tower (1971) cites 10 percent as the
upper limit to the index of the marginal welfare
cost per dollar revenue for other distorting taxes.
This estimate is considerably lower than those
of Ballard, Shoven and Whally (1985), which
range from 17 to 56. We assume 10 percent as
the marginal welfare cost per dollar of revenue
for other distortionary taxes. Using the Cagan
function, we have in a currency-only world
(8 )
dW
dR
ib
1 -ib ’
where dW/dR = 5i/(l-5i) = .1 and i* = .018. With
the real rate = 0.015, the “optimal” inflation rate
is approximately zero. Given the parameter values
we have assumed, a very modest tax on real bal
ances equalizes the marginal welfare cost per
dollar of revenue to an index of distortions due
to other taxes.
THE MARGINAL WELFARE COST OF
REVENUE: COMPETITIVELY PRICED
DEPOSITS ONLY
A variant of the above formula holds for a large
number of competitive banks subject to a
sterile legal reserve requirement, /, (Marty and
Chaloupka, 1988). An individual bank would
be forced by competition to pay (1 -f)i on its
69
deposits where i is the yield on its assets. The
opportunity cost of holding deposits is then fi.
In a deposit-only world, the welfare cost becomes
(9) W = j(p [x )d x - if(p[if).
The marginal change to welfare due to inflation is
ai
In this case, revenue is
With the real rate equal to 1.5 percent, the
“optimal” rate of inflation is 12.3 percent.
THE MARGINAL WELFARE COST OF
REVENUE FROM INFLATION: CUR
RENCY AND COMPETITIVELY PRICED
DEPOSITS
We now show that the above analysis can be
extended to a world of both currency and deposits.
The demand function for each component is still
referred to as <p, but they are potentially different
and the different measure of cost, i or if, is used
to indicate this. The counterpart measures are
(11) R = fi(p{if).
' i
\
( if
j(p (x )d x -i(p (i) + j(p [x )d x -if(p U f )
(14)W :
The marginal increment to revenue as the interest
rate changes, dR/di, is the bracketed term in
equation 10. Since the elasticity of demand for
deposits is
(15 ) ^
(12) Nlf = - f i v V f )
(16) R = i(p[i) + if(p[if),
the marginal welfare cost per dollar increment
to revenue is
(17) - j r = i<p'[i) + (p[i) + if(p '[if)f + (p [if) f
Vo
/
V0
dW
= - i (p ' [ i) - if( p ' [ if) f,
di
(pUf)
flJ D
(13)
dW / di
d R /d i
Ny
1 -A L
di
and
dW
dR
(18)
(p[i) + icp'[i) + iffcp'[f) + f(p [if) '
Since
The authorities in a bank-only world can
set a money rate of interest equal to that in the
currency-only world divided by the reciprocal
of the reserve ratio, /. If the optimal money rate
in the currency world were 10 percent, that rate
can be set at 40 percent in a world of deposits
(assuming the reserve ratio is 25 percent). Both
the welfare loss and the tax revenue, however,
are the same as in a currency-only world.
Although the tax rate (the money rate of interest)
is higher by the reciprocal of the reserve ratio, the
tax base is reduced by the share of high powered
money in the total money supply f[M/P).
Assume initially that the demand for deposits
has the same functional form as that for currency,
that the marginal welfare costs per dollar of rev
enue for other distortionary taxes is the same as
in the world of currency, and that the reserve
ratio is 13 percent (realistic for the United States).
Since dW/dR = ifb/{l-ifb), we have .1 = i(.13)5/
[1 - j (.13)(5)] then i* = 13.8 percent, which is equal
to the money rate in a world of currency, 1.8 per
cent, divided by the reserve ratio, 13 percent.
(19) Nif =
(pdf)
we obtain
C
Nr
D
—
H
+—
fN if
sat
(20)
dW
dR
— [ l - N ,) + — f [ l - N if
M
1
MJ
,f
where C is currency, <p(i), and D is deposits, ip(/i').
Once again, set the index of the marginal wel
fare costs per dollar increment to revenue for
other distorting taxes equal to 0.1. Let the
reserve ratio be 13 percent and ratio of currency
to the money supply be 30 percent (the ratio of
bank deposits to money is then 70 percent).
These figures correspond broadly to ratios in
place in the United States for the early 1990s.
Again set the semi-log slope of the Cagan func
tion equal to 5. Then we have dW/dR = [(.3) (5i)
+ .7 (.65i) (-13)]/{(.3 - 1.5i) + .091 [1 - (,13)(5i)]} =
0.1. Then i* = 2.28 percent. It should be noted
JULY/AUGUST 1994
70
that, although the formula is a weighted average
of currency and deposits, the currency weight
dominates the solution. W hile demand deposits
are 70 percent of the money supply, the tax base
is only the ratio of reserves to the money supply
—that is, 9 percent. Given this low reserve
ratio, currency commands dominate weight.
The formula makes intuitive sense. If the rev
enue ratio equals 100 percent, so that demand
deposits pay no interest and, assuming for sim
plicity, that the demand function (cp) for deposits
is the same as that for currency, the formula
reduces to
(21)
--- Nj + --- N:
M ' M '
dW
dR
N,
l-iV ;
In effect, currency and deposits are of the same
stuff.
On the other hand, if the reserve ratio is zero,
deposits produce neither seignorage nor a wel
fare loss; we are, in effect, in a currency-only
world because the monetary authority receives
no revenue from deposits. In this case, the
formula reduces to
(2 2 )
dW
dR
1 - N,
This again makes intuitive sense since only
currency is taxable.
Variants of the above formulas can be derived.
Consider, for example, a world in which an
effective prohibition on the payment of interest
on deposits is in effect. Then
i
i
(23) W = | (p(x)dx - i(p{i)+ J (p(x)dx - i(p(i)
0
0
and
(24) R = i(p{i) + if(p[i).
It follows that
(25)
dW
C
D
---N; + --- N;
M ' M '
dR
— ( l- iV ,) + — /(1 -JV ,.)
M
'
M
This is similar to the formula in equation 20,
where deposits pay interest, but without the
FEDERAL RESERVE BANK OF ST. LOUIS
reserve ratio, /, in the second term of the numer
ator. If the reserve ratio equals zero and there is
no interest paid on deposits, bank deposits yield
no government revenue, but a welfare loss accrues
to both currency and deposits. If the reserve ratio
equals 100 percent, the interest prohibition on
deposits is unnecessary, but both currency and
deposits incur a welfare loss and both provide
seignorage. Once again, the formulas make
intuitive sense.
CONCLUSIONS AND COMMENTARY
The above analysis has imposed the zero-profit
condition that the return on interest-bearing assets
is paid out in interest on deposits. This condition
ignores the bank’s intermediation function, which
has a necessary supply price. If the marginal costs
of intermediation are constant, the interest paid
on deposits is reduced by a given proportion.
Since the tax base (reserves) is independent of
intermediation costs, but deposits pay less interest,
it follows that we have underestimated somewhat
the marginal welfare costs and have erred on the
side of overestimating the optimal rate of inflation.
Although for purposes of exposition, the analy
sis has in the main assumed that the demand
schedule for deposits is the same as that for
currency, all the formulas hold if the demand
schedule for deposits differs from that for cur
rency. All one needs to do is change the form
of the function and plug in the relevant interest
elasticities. The formulas are general and can
be applied to economies with different indexes
of marginal distortions and varying interest
elasticities.
A potential problem in using these formulas
to predict dW/dR is that the ratio of currency
to deposits may change with the rate of inflation.
As an empirical matter, the currency-deposit
ratio has remained remarkably stable in the
United States since the period of financial de
regulation in the late ’80s, when deposits began
paying explicit interest. Moreover, a theoretical
argument that the currency-deposit ratio is inde
pendent of the money rate of interest has been
made by Dwyer and Saving (1986). As we have
seen the opportunity cost of holding currency is
the rate of interest, i, and the opportunity cost of
holding deposits is a fraction of the interest rate,
if. Assuming the indifference curve between
currency and deposits are homothetic, and that
the ratio of these opportunity costs is the appro
priate measure (by analogy with price theory)
71
determining the currency deposit ratio, this ratio
is independent of the money rate of interest.2
Although these formulas have been used to
assess dW/dR at hypothetical inflation rates,
which requires predicting the currency deposit
ratio, the formulas also can be used to calculate
the ex post measure dW/dR at a prevailing money
rate. All that is required is to observe the pre
vailing currency-deposit ratio.
Finally, some caveats are in order. The analysis
deals with alternative positions of steady-state
inflation. It does not handle the welfare costs of
variable inflation—costs which may well be more
significant than those associated with steady-state
inflation. Moreover, our analysis has treated real
balances as part of an optimal tax menu; this usual
assumption is not without its critics (Lucas, 1986).
REFERENCES
Auemheimer, Leonardo. “The Honest Government’s Guide
to the Revenue from the Creation of Money,” Journal of
Political Economy (May/June 1974), pp. 598-606.
Ballard, Charles L., John B. Shoven, and John Whalley.
“General Equilibrium Computations of the Marginal Welfare
2 This reasoning, however, is not fully compelling. The ratio of
the price of sowbellies to that of caviar has the dimensionali
ty of sowbellies to caviar and is independent of proportionate
changes which leave the relative price ratio unchanged.
The ratio of the opportunity cost of currency to that of
deposits is a dimensionless number and taking the ratio of
the opportunity costs (by analogy with commodities) implies
that one’s choice of currency and deposits is independent of
the difference in their opportunity costs.
Tatom (1979) makes an early attempt to determine the
marginal welfare costs per dollar of revenue in a world of
both currency and deposits. He takes the ratio of the oppor
tunity costs combined with homothetic indifference curves as
Costs of Taxes in the United States,” The American
Economic Review (March 1985), pp. 128-38.
Dwyer, Gerald P. Jr., and Thomas R. Saving. “Government
Revenue from Money Creation with Government and Private
Money,” Journal o f Monetary Economics (March 1986),
pp. 239-49.
Friedman, Milton. “Government Revenue from Inflation,”
Journal o f Political Economy (July/August 1971), pp. 846-56.
Lucas, Robert E., Jr. “Principles of Fiscal and Monetary Policy,”
Journal o f Monetary Economics (January 1986), pp. 117-34.
Marty, Alvin L. “A Note on the Welfare Cost of Money Creation,”
Journal o f Monetary Economics (January 1976), pp. 121-4.
_____ , and Frank J. Chaloupka. “Optimal Inflation Rates: A
Generalization," Journal o f Money, Credit and Banking
(February 1988), pp. 141-4.
Phelps, Edmund S. “Inflation in the Theory of Public Finance,”
Swedish Journal o f Economics (March 1973), pp. 67-82.
Ramsey, Frank. P. “A Contribution to the Theory of Taxation,”
Economic Journal (March 1927), pp. 47-61.
Tatom, John A. “The Marginal Welfare Cost of the Revenue
from Money Creation and the ‘Optimal’ Rate of Inflation,"
The Manchester School o f Economic and Social Studies
(December 1979), pp. 359-68.
Tower, Edward. “More on the Welfare Cost of Inflationary
Finance,” Journal o f Money, Credit and Banking (November
1971), pp. 850-60.
a compelling reason to treat the currency-deposits ratio as
independent of the inflation rate. More importantly, Tatom
does not build up his welfare costs from an explicit consider
ation of the integral for currency and deposits separately, but
conflates the two using a single integral running from zero to
the money rate of interest. In fact, the integral for competi
tively priced deposits should run from zero to if. Interestingly
enough, Tatom’s analysis, although not general, applies to a
world in which an effective prohibition on the payment of
interest on deposits exists, and in which the form of the
demand schedule is the same for currency and deposits.
This is a special case of my analysis, and I am indebted to
John Tatom for this reference and discussion.
JULY/AUGUST 1994
@FedFRASER