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3 T w o Faces of Financial Innovation
18 The Recent Credit Crunch:
The Neglected Dim ensions
37 Structural Approaches to
Vector Autoregressions
58 The Misuse of the Fed’s
Discount W in d ow

THE
FEDERAL
A RESERVE
JZkRANK of
A r ST.IXH IS

1

Federal Reserve Bank of St. Louis
R e v ie w

September/October 1992

In This Issue . . .




Innovation has always been a hallmark o f the financial services indus­
try. Recent innovations range from new mechanical devices and new
contractual arrangements to new operational procedures. In response to
the pace and diversity o f financial innovation, researchers have studied
the econom ics o f this innovation. One approach focuses on improving
financial products by applying the principles o f finance theory to the
process o f contract design in securities markets. A second approach fo ­
cuses on the reasons why financial innovation occurs, examining the in­
centives for people to develop new financial contracts or technologies.
In the first article in this Review, "T w o Faces o f Financial Innovation,"
Mark D. Flood uses tw o case studies to illustrate how financial innova­
tions are developed to meet a perceived demand for new financial serv­
ices. The tw o cases presented illustrate h ow market forces can spell
failure for product designs that do not incorporate the principles of
financial theory and success for those that do.
* * *
Although the notion o f a credit crunch is not new, its widespread use
with reference to the latest recession and recovery has been the con­
ventional wisdom in many policy circles. In the second article in this is­
sue, "The Recent Credit Crunch: The Neglected Dimensions,” Kevin L.
Kliesen and John A. Tatom take a historical view o f credit crunches and
their relevance to the nation’s cyclical perform ance. They explain the
origins o f the credit crunch concept and point to the consistent misap­
plication o f the concept to cyclical credit market developments. For ex­
ample, they show that movements o f interest rates and o f interest rate
spreads in recessions generally have not provided support for the credit
crunch hypothesis. The most recent case is no exception.
According to the authors, the recent decline in the growth o f credit is
mostly attributable to tw o factors that are inextricably linked. First, the
demand for credit, especially by business, is cyclical. W hen econom ic ac­
tivity ebbs in a recession, the demand for credit falls as well. Second,
because bank lending to business is typically short term, it is used to
finance short-term assets such as inventory. Thus when businesses ex­
pect their sales to slow or decline in a recession, they no longer need to
add to their stocks o f inventory. Accordingly, business inventories and
the demand for bank credit to finance them are reduced. Similarly, in
the early stages o f an econom ic expansion, when businesses add to in­
ventory holdings, they typically rely relatively more on internal cash
flow and other sources o f financing, than on bank loans. Only later do
businesses begin to expand bank borrow ing in line with their burgeoning
financial requirements.

SEPTEMBER/OCTOBER 1992

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The authors maintain that in the final analysis, the conventional wisdom
espoused by credit crunch theorists is not helpful in assessing recent
movements o f interest rates, business loans and business inventories.
*

*

*

Vector autoregressive (VAR) models are frequently used to estimate
dynamic relationships for econom ic data. Initially the VAR was not in­
tended to describe structural mechanisms because it represents a
reduced form. An econom ic interpretation o f these empirical models,
however, does require a set o f structural assumptions.
In the third article in this issue, "Structural Approaches to Vector Autoregressions,” John W. Keating reviews the principles o f VAR analysis
with particular emphasis on tw o structural VAR approaches. The two
approaches impose restrictions on contemporaneous and long-run be­
havior to identify a structural model from the reduced form. The
author provides empirical examples with a standard group o f m acroeco­
nomic variables to illustrate these tw o approaches. The empirical longrun structural model yields results that are generally consistent with the
theoretical model, whereas the results for the contem poraneous model
are frequently inconsistent with theory. These findings suggest that
long-run structural VAR models are superior; however, additional inves­
tigation should determine whether this result is robust or simply a spe­
cial case.
* * *
In the final article in this Review, "The Misuse o f the Fed’s Discount
W indow ,” Anna J. Schwartz, a senior research associate at the National
Bureau o f Economic Research, asks not only whether the Fed's discount
w indow continues to serve any useful function, but also whether its
operation may have unintended adverse effects. The discount rate, for
example, draws widespread—but in Schwartz's view, misdirected—
attention as an indicator o f the thrust o f monetary policy. Schwartz is
also concerned about the many, albeit unsuccessful, attempts to extend
the Fed’s lender-of-last-resort function to nonbank firms. Most im por­
tant, however, is her concern that in recent years the discount window
has extended credit to banks that w ere insolvent or near insolvency—a
practice that she argues has increased taxpayer losses associated with
reimbursing insured depositors at failed banks. Although many analysts
will find some o f her arguments controversial, Schwartz raises a num­
ber o f issues w orthy o f further research.


FEDERAL RESERVE BANK OF ST. LOUIS


*

*

*

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Mark D. Flood
Mark D. Flood is an economist at the Federal Reserve Bank
of St. Louis. David H. Kelly and James P. Kelley provided
research assistance.

Two Faces of Financial
Innovation

I n n o v a t io n h a s ALWAYS been a hallmark
o f the financial services industry. Indeed, the
history o f finance can be organized as a chroni­
cle of innovations. W e can trace this history
from the introduction o f coinage in the Greek
state o f Lydia in the 7th century B.C., through
the various ploys to circumvent the Christian
and Islamic bans on usury in the medieval era,
through the development o f modern systems o f
insurance in the 18th and 19th centuries, on up
to m ore timely innovations such as foreign cur­
rency exchange warrants and interest-rate
swaps.1
Recent innovations have ranged from the
comm onplace — the automatic teller machine
(ATM), for example — to the arcane — exchangetraded options to buy futures contracts on
municipal bond index funds. Indeed, the range
o f innovation, from new mechanical devices to
new contractual arrangements to new opera­
tional procedures, is so broad as to confound
concise definition o f the term.2 M oreover, inno­
1See Goldsmith (1987) for some descriptions of financial in­
stitutions and instruments throughout history.
2Schumpeter (1939) defines an innovation as a change in
the shape of the production function. He goes on to
categorize innovations as being either “ process” or
“ product.” Process refers to innovations that permit an ex­
isting product or service to be provided more cheaply.
Product refers to innovations that introduce a product or
service that was previously unavailable. The ATM, for ex­
ample, is a mixture of both types. An ATM provides many
routine services, such as accepting deposits and disburs-




vations have recently arrived at a frenetic pace;
in the narrow field o f exchange-traded futures,
for example, Silber (1981) lists 102 new con ­
tracts introduced in the United States in the
1970s alone.
In response to the pace and diversity o f finan­
cial innovation, economists have studied the eco­
nomics o f innovation. Tw o largely distinct — but
not necessarily inconsistent — approaches to the
subject have developed over the last 20 years.
One approach, motivated by the imperfect suc­
cess rate fo r new securities, has focused on
improving financial products by applying the
principles o f finance theory to the process of
contract design in securities markets.3 The sec­
ond approach, motivated largely by central
bankers’ concerns about the effect o f innova­
tions on monetary policy, has focused on the
reasons w hy financial innovation occurs. This
approach has examined the incentives for people
to develop new financial contracts or technolo­
gies.4 Using tw o case studies, this paper illusing withdrawals, and usually does so more cheaply. At the
same time, an ATM can provide services that were previ­
ously unavailable, such as nighttime and weekend with­
drawals.
3Some examples are Allen and Gale (1988), Chen and Kensinger (1990), Johnston and McConnell (1989), and Silber
(1981).
4Some examples are Goodhart (1986), Kane (1984), Podolski
(1986), Rasche (1988), and Simpson (1984).

SEPTEMBER/OCTOBER 1992

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trates h ow financial innovations arise to meet a
perceived demand for new financial services.
The contrasting experience o f the tw o cases
shows how market forces can spell failure for
product designs that do not attend to the princi­
ples o f financial theory and success for those
that do.

W H Y IN N O VA TIO N OCCURS
In general, individuals do not innovate out of
a spirit o f magnanimity. Indeed, w e shall assume,
as we do with other econom ic behavior, that
financial innovations are created in anticipation
o f material gain. Most theories o f the incentives
to innovate can be understood in terms o f a
cost-benefit analysis: new potential profits are
the incentives to innovate. These arise when a
change occurs that makes possible either a
reduction in costs, an increase in revenues, or
both. For simplicity, such changes are usually
treated as occurring exogenously to the finan­
cial services industry, even when this depiction
is not entirely accurate.
On the cost-reduction side o f the cost-benefit in­
terpretation, exogenous technological change is
the force most often cited as producing the
potential cost reductions that can induce innova­
tion. As w e shall see below, the transaction
costs and the costs o f market illiquidity are two
factors that frequently affect the production
and success o f financial innovations. Advances
in computing pow er, for example, have lowered
the cost o f such accounting-intensive products
as brokered deposits and mutual funds. Other
products relying on rapid calculation and deci­
sion, such as portfolio insurance and index arbi­
trage transactions, have similarly been made
feasible by increases in com puter speed. The
ATM, w hich reduces bank operating costs by ef­
ficiently executing much o f a teller’s drudgery,
was made possible by gains in both computing
pow er and miniaturization.
Some o f these innovations can also illustrate
the other side o f the incentive to innovate — the
potential for increased revenues. Activities like
index arbitrage w ould be inconceivable without
some form o f reliable, high-speed calculation;
computers can thus be seen either as reducing
5See, for example, Kane (1984) or Miller (1986).
6See Marton (1984), p. 239. Alchian (1977), pp. 30-32, dis­
cusses the role of trial and error in the process of innova­
tion, and he equates success with survival. He notes (p.
31) that “ the available evidence [that the necessary condi­

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FEDERAL


the potential cost o f the activity from infinity or
as increasing potential revenues above zero.
More commonly cited as forces that can
generate potential sources o f new revenue are
government policy and inflation.5 The tax code,
in particular, offers numerous incentives. Tax­
payers innovate to exploit loopholes and avoid
assessments (for example, tax-free municipal
bond mutual funds). If taxpayers are successful
in using financial innovations to low er their tax
bills, government may seek to re-legislate to
close loopholes and expand the scope o f taxa­
tion. Completing the cycle — in what Kane
(1977) has called the "regulatory dialectic" —
taxpayers find new incentives in the revised tax
code and innovate again. Broad-based m acroeco­
nomic factors can also motivate innovation. For
example, inflation com bined with deposit in­
terest rate ceilings in the late 1970s and early
1980s to produce new kinds o f bank deposits —
super-NOW accounts and money-market mutual
funds — w hich function essentially as interestbearing checking accounts. M ore recently, the
Coffee, Sugar and Cocoa Exchange experiment­
ed unsuccessfully with consum er price index
(CPI) futures, w hich w ere to hav^ allowed inves­
tors to hedge against inflation.

W H Y PA R TIC U LAR IN N O VATION S
SUCCEED
Creators o f financial innovations are obviously
interested in whether their innovations will suc­
ceed in the marketplace. Success, o f course, is
not automatic. For example, as Marton reports,
"some exchange officials privately admit that
they put out new futures products pretty much
the way a cook tests his spaghetti strands — by
flinging them against the wall to see if any of
them stick.”6 Because innovation is not costless,
however, it is important that innovators have a
m ore systematic approach to innovation than
primitive trial and error.
To examine the successfulness o f specific in­
novations, w e must first have some way of
measuring success. Because w e have assumed
that people innovate in hopes o f profit, a mea­
sure o f success should either measure the innotions are met under which trial and error converges to a
profit-maximizing equilibrium] seems overwhelmingly un­
favorable.” For our purposes, defining success as survival
is not precise enough to be useful, since even failures will
survive at least briefly before their demise.

5

vator’s profits directly or, at least, be correlated
with those profits. In many cases, a measure of
popularity can proxy for success. For example,
an exchange that introduces a new security
might measure success by dollar trading volume
in the new contract. Given a measure for suc­
cess, innovators can set about designing a pro­
duct to maximize that measure.
Some o f the factors leading to a successful in­
novation are illustrated in the following exam­
ple. The economist Milton Friedman, anticipating
a devaluation o f the British pound in the early
1970s, discovered he could not speculate on his
beliefs, because no bank would allow him to sell
the pound short. Hearing o f his plight (and
presuming that his predicament was not
unique), Leo Melamed and the Chicago Mercan­
tile Exchange (CME) launched the International
Monetary Market (IMM). The IMM trades, among
other things, foreign currency futures, which al­
low investors to speculate on devaluations (or
appreciations) o f the pound. This innovation has
been successful because the CME found a trade
that investors wanted to make, but could not,
and it devised an instrument that allows them
to do so cheaply and reliably (an exchangetraded foreign currency futures contract).7

subtleties can play a role in determining the
success or failure o f a new financial product.
These issues play a prominent role in our first
case study.
Nonetheless, some rules o f thumb do exist for
identifying likely successes in futures markets:
contracts based on commodities that are easily
standardized, have large price volatility, and
have enough suppliers and demanders to create
a liquid market.10 These rules are far from fool­
proof, however. Moreover, they do not general­
ize automatically to other types o f innovations.
Indeed, codification o f the elements o f success­
ful innovation as a collection o f rules is almost
certainly impossible; it is also beyond the scope
o f this paper. Instead, w e illustrate with tw o
case studies the more general ideas o f the in­
centives to innovate and the application of
financial principles to real innovations.

CASE 1, A FAILURE:
CAN AD IAN COIN FUTURES
The first innovation we consider is a futures
contract on bagged Canadian silver coins, in­
troduced by the IMM. This innovation was a
failure. After 13 months o f meager trading, the
IMM discontinued the unpopular and unprofit­
able contract. W hy did this contract fail? There
is an answer that is consistent with both our
theoretical rationales for successful financial in­
novation and with the facts: A good cross-hedge
existed in the much more liquid silver futures
market. There, hedgers could achieve similar
results at low er cost.

A m ore general application o f this recipe for
success must answer several questions. For ex­
ample, how is an innovator to know w hich as
yet non-existent security investors want to
trade? A full answer to this requires considera­
ble insight into investor demand. Famous
economists may offer suggestions, but this
process is not always reliable. Milton Friedman,
for example, also advocated the failed CPI fu­
tures contract.8

A Description o f the Instrument

A secondary problem is knowing whether in­
vestors can already make a certain type o f trade.
While the answer might seem readily obtainable,
the existence o f substitutes is not always obvi­
ous. In the futures markets, for example, hedg­
ing a com modity position with a futures
contract on a close substitute (cross-hedging)
may be adequate or even superior to hedging
directly.9 Identifying these possibilities and how
they might be used can be quite subtle. Such

On October 1, 1973, the IMM opened trading
in a new futures contract on Canadian silver
coins. The purchaser o f a contract promised to
pay a certain future amount in U. S. dollars
(USD) at a specific future maturity date; in ex­
change, the purchaser would receive future
delivery o f five bags o f Canadian silver coins
(dimes, quarters or half-dollars), with each bag
w orth 1,000 Canadian dollars (CAD) at face
value. Different denominations could not be

7See Miller (1986), p. 464. Similar speculation was possible
in the interbank market for forward foreign exchange. In­
dividual investors, like Friedman, are generally excluded
from this market, however.
Innovations like this, that expand the possibilities for ex­
change, are generally Pareto-improving. That is, they can
make everyone involved better off. See, for example, Flood
(1991).

9A useful concept in this regard is “ redundancy.” If the
price of a good is always a fixed multiple of the price of
another good, so that the price changes for the two are al­
ways perfectly correlated, then one of the goods is said to
be redundant.
'°See Black (1986), pp. 5-12.

8See Friedman (1984).



SEPTEMBER/OCTOBER 1992

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mixed within a bag, and the coins w ere to have
been minted before 1967, with the exception
that a bag could contain up to 2 percent 1967
or 1968 coins containing at least 50 percent sil­
ver.11

words, we can explain failure by establishing
the existence o f an efficient cross-hedge for the
futures contract. It turns out that, subject to
some caveats, we can demonstrate that the
coinage contract was indeed redundant.

The contract was presumably intended to af­
ford commercial banks holding vault inventories
o f silver coinage the opportunity to hedge their
positions. In the mid-1960s, both the United
States and Canada had phased out the use o f sil­
ver in their coinage. In an application of
Gresham's Law — "Bad m oney drives out good”
— both banks and private investors hoarded sil­
ver coins for the bullion content, using instead
the new, non-silver coinage as a transactions
medium.12

In doing this, it would be helpful to under­
stand theoretically w hy the price o f the cross­
hedging instrument should be correlated with
the price of the coinage futures contract. With
this in mind, we examine the dual role (as either
silver or currency) o f the coins more closely.

The hoarded Canadian silver coins might be
valuable for tw o reasons. First, they w ere Cana­
dian currency and, therefore, could be ex­
changed for goods and services in Canada.
Second, they contained substantial amounts of
silver, a mineral with numerous industrial uses.13
Therefore, their USD value could fluctuate with
changes in the USD/CAD exchange rate or with
changes in the USD price o f silver. Banks wish­
ing to protect themselves against such price
fluctuations could simply sell their stores o f the
coins, or they could sell the new futures con ­
tracts, which would lock in a future sale price
for their inventory. As w e shall see, however,
indirect hedges w ere also available.

Redundancy
W e are interested in factors contributing to
the failure o f the IMM’s futures contract on the
coins. One way to explain this failure w ould be
to find some other security that provides the
same risk allocation m ore cheaply. In other

11See IMM (1973a), p. 22. Because the payoffs described
here are all in U. S. dollars, it may be helpful to imagine
that the hedging institution is a U. S. bank. Regardless,
the nationality of the parties involved should not affect in
any way the pricing relationships discussed below.
12The new coins consisted of a copper core clad in a
copper-nickel alloy; they contained no silver. The Board of
Governors of the Federal Reserve (1970) ruled that vault in­
ventories of U. S. silver coins held by commercial banks for
their own account could still be counted as part of required
reserves, even though they were being hoarded and there­
fore would not circulate. Coins to which the bank did not
have “ the full and unrestricted right” — for example, coins
held for safekeeping in the name of a speculating deposi­
tor — would not satisfy reserve requirements.
13IMM (1973a), p. 20, suggested that the numismatic value of
the coins might also be a factor. The possibility that
bagged coins might have significant numismatic value is

http://fraser.stlouisfed.org/
FEDERAL RESERVE BANK OF ST. LOUIS
Federal Reserve Bank of St. Louis

At any time, the coins could be used for one
of tw o purposes: as a stock o f raw silver for in­
dustrial purposes, or as a medium o f exchange
for transaction purposes. The coins clearly
could not be used for both purposes simulta­
neously: industrial use w ould require melting the
coins; monetary use would require not melting
them. Instead, if the coins w ere rem oved from
bank vaults and put to use, w e should expect
them to go to the m ore valuable o f the tw o uses.
These relationships are presented in figure 1.
This surface is a plot o f the value o f coins as a
function o f the USD/CAD exchange rate and the
USD value o f silver. Given coordinates for the
USD value o f silver and the USD value o f Cana­
dian dollars, the height o f the surface at that
point is the value o f the bagged Canadian coins.
The graph formalizes the notion that the silver
coins are worth the larger o f tw o values: their
value as silver or Canadian currency. The axes
are scaled to correspond to contract specifica­
tions in the futures markets. The units on the
CAD axis give the USD value o f CAD 100,000,
the contract size for a foreign exchange futures
contract. Similarly, the silver axis gives the USD
value o f 5,000 troy oz. o f silver, the contract
size for a silver futures contract at the Chicago

remote, however. Collectors grade coins according to quali­
ty (e. g., proof, uncirculated, very fine, etc.). With rare ex­
ceptions, coins of recent minting are priced above face
value, only if they are rated as proof or uncirculated. The
fact that the coins subject to the futures contract were
poured loose into bags implies that they could not be rated
proof or uncirculated. Indeed, the “sweating” of coins, i. e.,
shaking them loose in a bag to rub off silver shavings, is a
traditional means of debasing a currency. The ABA (1965),
p. 8, for example, claimed that it was “obvious that it will
be years and years before these coins have any value as
collectors’ items.”

7

Figure 1

Theoretical Relationship Between Spot Prices

USD per 5
bags o f coins

200000

150000

100000
USD per CAD 100,000
50000
USD per 5,000 oz. silver

Board o f Trade (CBOT). The surface is a graph
o f the function:
Vct = max {0.05Vdt, 0.579Vst},
where \£, is the USD value o f the five bags o f
coins at time t, Vdt is the USD value o f CAD
100,000, and Vst is the USD value o f 5,000 troy
oz. o f silver.14
While this equation describes the relationships
among spot prices for the three commodities, it
14The coefficients, 0.05 and 0.579, are simply the proportions
of CAD 100,000 and 5,000 troy oz. of silver, respectively,
present in five bags of coins. The contract requires that the
coins are worth CAD 5,000 at face value, or 5 percent of
CAD 100,000. The contract also specifies that “ The coins
must bear a minting date of 1966 or earlier, except that an
individual bag may contain up to 2% 1967 or 1968 coins
containing at least 50% silver ... The gross weight of
each bag, including bag, seal, and tag shall not be less
than 50.75 pounds [avoirdupois] for each [CAD] $1,000 face
amount;” emphasis in the original, IMM (1973b), p. 2.
(Coins minted prior to 1967 were 80 percent silver by
weight.) Deducting 0.75 pounds for the weight of the bag,
and assuming that banks applied Gresham’s law, that is,
they chose their coins to minimize



does not address the price o f the coinage fu­
tures contract directly. Tw o facts are relevant
to our investigation at this point: First, futures
contracts for both Canadian dollars and silver
w ere actively traded at the time; second, the
price o f any futures contract must converge to
the corresponding com m odity spot price on the
maturity date o f the futures contract. The latter
condition holds because, at maturity, arbitrage
ensures that a contract for future delivery ef­
fectively becom es a contract for spot delivery.15
the silver content of each bag within the constraints of the
contract, we find that each bag (CAD 1,000 face value)
contained 39.7 lbs., or 578.9 troy oz. of silver. Thus, five
bags contained 57.89 percent of 5,000 troy oz. of silver.
15For example, if the price of a maturing futures contract sig­
nificantly exceeded the spot commodity price, then an ar­
bitrageur could make unlimited, riskless profits by selling
futures, buying spot and delivering the commodity. There
is some margin for price discrepancies: this arbitrage is
only profitable if the price difference exceeds the costs of
transaction and delivery. Still, only one arbitrageur is need­
ed to enforce the arbitrage; the delivery and transaction
costs for the least-cost arbitrageur should be the only rele­
vant ones in this context.

SEPTEMBER/OCTOBER 1992

8

Figure 2

Daily Spot Prices of Silver and Canadian Dollars
U.S. $ per 100,000 Canadian dollars

U.S. $ per 100,000 Canadian dollars

$ U.S. per 5,000 oz. Silver

Given these relationships, w e can restate our
equation (approximately) in terms o f the matur­
ing futures contracts:
VcT ~ max {0.0 51^T, 0.579Kr}<
w here VcT is the USD value o f the coinage fu­
tures at the maturity date, T, VdT is the USD
value o f CAD futures, and Kt is the USD value
o f the silver futures. Assuming that delivery
and transaction costs are negligible makes this
equation exact: l£x = max {0.05l£T, 0.5791{X}.
This equation holds only at the maturity date of
the futures contracts, however. At maturity,
there is no uncertainty about which is larger,
0.05ViT or 0.579!£t . Before maturity, l£T and
are uncertain.16
As it turns out, this latter complication is
largely academic. In hindsight, over the life o f
16We can still establish certain relationships between the
prices, however. For times t < T, the possibility that the
coins might be more valuable as currency than as silver
provides a price floor for the coinage futures in terms of
the silver futures: Vc, > 0.579Vst. Similarly, we have a price
floor for the coinage futures in terms of Canadian dollar fu­
tures: Vct > 0.05Vdt. Finally, because holding both silver
and Canadian dollars at maturity must always be prefera-


FEDERAL RESERVE BANK OF ST. LOUIS


the coinage futures contracts, the coins w ere
never m ore valuable as currency than they w ere
as silver. Figure 2 graphs daily observations
(scaled as in figure 1) o f spot silver prices and
the USD/CAD spot exchange rate for October
1973 through June 1974. The line in the graph
corresponds to the crease in the surface o f fig­
ure l . 17 The fact that all points fall to the right
o f the line means that max{0.05Vdt, 0.579Vst} was
always 0.579VS, (that is, that 0.579Vsl > 0.05Vdt).
More significantly, it appears that, even b e­
fore the fact, investors considered an outcome
to the left o f the line to be highly unlikely. If
the probability o f such an outcom e is negligible
(that is, if the probability is small that
0.05Vdt > 0.579VJ, then it is safe to use the ap­
proximation: max{0.05Vdt, 0.579Vst} ~ 0.579Vst.
M oreover, if this approximation always holds in
the spot markets, it should also hold for futures
ble to holding only the more valuable of the two, we can
readily establish a price ceiling: Vct < 0.579Vsl + 0.05Vdt.
17The crease in figure 1 is the set of points satisfying both
Vc = 0.05Vd, and Vct = 0.579Vst. Thus, it is the line defined
by 0.05Vdt = Vct = 0.579Vst, or Vdt = (0.579/0.05)Vst. This is
the line graphed in figure 2.

9

Figure 3

Daily Futures Prices for Silver and Canadian Coins
Price of Canadian coinage futures

Price of silver futures

0 0 0

contracts; this implies w e can use the approxi­
mation Va ~ 0.579V„.
The upshot o f this is that, as long as investors
could safely ignore the possibility that the coins
would be m ore valuable as currency, a silver
futures contract was a good cross-hedge for the
coins. In other words, the value o f the coins
would be determined solely by their silver con­
tent, rather than their potential use as Canadian
currency — the value o f the coins should move
in tandem with silver prices. Conversely, if all
the points w ere to lie on the left side o f the line
in figure 2 instead o f the right, the opposite
condition would hold: the CAD futures con ­
tract would be the appropriate cross-hedge to

June contracts

O O O December contracts

consider, and w e could disregard the silver
contract.
The usefulness o f silver futures as a crosshedge is confirm ed in figures 3 and 4. Figure 3
plots daily price observations for silver futures
and Canadian coinage futures maturing in June
1974 and Decem ber 1974. The bold line through
the origin is the theoretical relationship under
redundancy: Va = 0.579
The other tw o lines are regression lines (lines
o f best fit) for the tw o different maturities.18
Given our regression results, w e can be more
specific about the effectiveness o f a cross-hedge.
The coefficient o f determination, or R2 statistic,
from such a regression is a standard measure of

18These regressions show that the behavior of silver futures
prices and that of coinage futures prices are very similar,
implying that these two potential hedging instruments are
essentially indistinguishable from a pricing standpoint. An
alternative would have been to demonstrate their hedging
effectiveness directly, by regressing spot coin prices first
on coinage futures prices and then on silver futures prices.
A spot price series for Canadian silver coins was not avail­
able, however.



SEPTEMBER/OCTOBER 1992

10

Figure 4
Daily Prices for December 1974 Silver and Canadian
Coin Futures
Price of Canadian coinage futures

the effectiveness o f a hedge. The R2 statistic can
vary from 0.00 for a useless hedge to 1.00 for a
perfect hedge. For the regressions on the June
and Decem ber contracts, the R2 statistics w ere
0.973 and 0.933, respectively.19 The implication
is that silver futures m oved closely together
with coinage futures, and thus could serve as
an excellent cross-hedge: Investors could have
achieved almost identical results with the silver
contract as with the coinage futures. This is
confirm ed in figure 4, which shows the same
relationship plotted as time series o f the two
prices. Silver and coinage futures prices moved
in near lockstep.20
19We can compare these numbers to the hedging effective­
ness of CAD futures. As expected, a regression of the
price of coinage futures on the price of CAD futures yields
lower R2 statistics, implying that silver futures were a better
cross-hedge. The Ft2 was 0.568 for the June contracts and
0.715 for December.
The use of the R2 originated with Ederington (1979), pp.
163-64. The standard measure is based on regressions of
returns on returns, rather than prices on prices, as are
shown in the figure. Because the coinage futures had no
recorded price on most days (due to no trading), however,
it was not possible to construct a daily return series. An
imperfect alternative is to calculate returns from one price
observation to the next, producing a time series of returns
with irregular holding periods. The R2 statistics for these

FEDERAL RESERVE BANK OF ST. LOUIS


Price of silver futures

Performance o f the Instrument
Having established the existence o f a service­
able cross-hedge for the Canadian coinage fu ­
tures contract, w e now examine the contract
from the perspective o f the innovator. From
this perspective, the contract is successful to
the extent that it profits the innovator. The in­
novator in this case was an organized futures
exchange, the IMM, ow ned by the members of
the exchange. The membership o f a futures ex­
change consists o f its traders, w h o benefit from
an increase in trading volume through higher
regressions are 0.385 for the June contract and 0.419 for
the December contract.
In comparison, Johnston and McConnell (1989) report on
Government National Mortgage Association (GNMA) Col­
lateralized Depository Receipt (CDR) futures contracts. Dur­
ing the most successful years of the contract, 1980-82, the
hedging effectiveness (R2) of the futures contract for the
underlying GNMA securities over five-day holding periods
ranged from .85 to .94. During the contract’s leanest years,
1983-85, the R2 ranged from .54 to .62 percent, making it a
less effective hedge than a Treasury bond futures contract.
20Because of low volume in the coinage futures market,
there were many days with no bids or offers submitted
and, therefore, no posted settlement prices.

11

turnover or through greater liquidity.21 For our
purposes, w e can proxy for profits by measur­
ing trading volume in the contract.
Illiquidity can be costly to traders in two
ways. First, traders may be forced to search ac­
tively for counterparties with w hom to trade;
searching consumes time and resources. Second,
traders w ho are delayed by the search process
face price risk: the price o f their commodity
can change before they locate a counterparty.
In general, a trader would require some re­
muneration before bearing such a risk willingly.
One o f the primary econom ic functions o f an
organized exchange is to bring traders together
in the same place, to obviate such search costs.
There is a recursive catch in the econom ic logic
here, however: traders may not be attracted to
a market if it is not liquid, but a market may
not be liquid unless traders are attracted to it.
Trading volumes for the June and Decem ber
coinage contracts, however, w ere never large.
On most days, few er than five contracts changed
hands. There w ere many days with no trades.
Of 183 trading days for the June contract, there
w ere 66 days when only a bid quote or only an
ask was available; neither was available on 78
days. For the Decem ber contract, 92 o f 310
trading days had only one side o f the market
present, and on 181 days neither side was
available.22 Trading volume peaked at 45 con ­
tracts on October 31, 1973; in comparison, for
the CBOT’s silver futures, several thousand con­
tracts changed hands on a good day in 1973.23
By October 1974, trading in the Canadian
coinage futures had dwindled to almost nothing.
The last recorded trade came on October 25,
1 9 7 4 , when a single Decem ber 1 9 7 4 contract
changed hands.
In hindsight, w e have a theoretical explana­
tion for the contract’s failure. Futures contracts
for Canadian silver coins should have been at­
21See Black (1986), pp. 19-21. There is no universally accept­
ed definition for the term “ liquidity.” It is usually associated
with an absence of search costs. See Demsetz (1968), Tinic (1972) and Logue (1975) for further discussion.

tractive to owners o f silver coins, w ho wanted
to hedge the value o f their coins against price
fluctuations, and speculators, w h o w ere willing
to bet they could predict those price changes
m ore accurately than the rest o f the market. A
comparison o f prices reveals that existing silver
futures w ere a close substitute for the coinage
futures as a hedging/speculating tool. Moreover,
the long-established silver contract traded in a
much more liquid market. Thus, hedgers and
speculators had in the silver contract most of
the benefits o f the coinage contract as a hedg­
ing instrument, without most o f the drawbacks
associated with illiquidity. In this context, then,
the silver futures should be seen as uniformly
preferable to the coinage futures.

CASE 2 , A SUCCESS:
M A R K E T INDEX M UTUAL FUNDS
W e turn now to a successful innovation: mar­
ket index mutual funds. The size o f the particu­
lar fund chosen as an example has grow n steadily
since its introduction in 1976. Although an index
fund is little m ore than a repackaging o f other
securities, with little decision-making discretion
left to the fund's management, such funds can
succeed by reducing the costs o f transacting for
individual investors.

A Description o f the Security
On August 31, 1976, the Vanguard Group in­
troduced the "500 Portfolio,” a stock market
mutual fund whose specific objective is to track
the Standard and Poor’s 500 stock market index
(S&P 500). In the language o f the fund’s
prospectus, "the 500 Portfolio seeks to replicate
the aggregate price and yield perform ance of
the Standard & Poor’s 500 Composite Stock
Price Index. ... The 500 Portfolio invests in all
500 stocks in the S&P 500 Index in approxiin October 1973. Again, in comparison, open interest for
the CBOT’s silver contract reached tens of thousands of
committed contracts during this time.

22Figure 4 includes prices for the coinage contract for many
days on which trading volume was zero. The exchange
posted settlement prices on many days when either bids or
offers appeared but no trading occurred.
23A related measure of the coinage contract’s lack of
popularity is open interest (the sum of all traders’ net long
positions in the contract, also called committed contracts).
The same picture of a thin and illiquid market emerges.
Open interest in the June 1974 contract peaked in May
1974 at 56 committed contracts. For the December 1974
contract, the peak of 37 committed contracts was reached



SEPTEMBER/OCTOBER 1992

12

mately the same proportions as they are
represented in the Index.”24
There are good reasons w hy w e might expect
a market index mutual fund to be unattractive
to investors. First, it is inflexible. For example,
an investor in an index fund w ho wanted to
divest any stake in, say, petroleum stocks would
have to sell her entire stake in the fund. In con­
trast, an investor holding the same stocks directly
could sell petroleum stocks without affecting
her other positions. Second, a mutual fund intro­
duces a middle man: The fund must be com pen­
sated for its investment management services,
which, for an index fund, are essentially papershuffling. The allocation o f assets in an index is
set by a predetermined rule, which an investor
could follow on his own.
On the other hand, there are also reasons
w hy investors might find an index fund attrac­
tive. First, despite the inflexibility o f rule-based
indexes, some investors might be attracted to a
specific index, so that the inflexibility o f that in­
dex would not be a binding constraint for those
investors. The standard capital asset pricing
model, for example, concludes that all investors
should hold a value-weighted portfolio o f all
available assets to achieve the best risk-return
trade-off.25 Although the S&P 500 does not con­
tain all assets, it is well diversified, it is valueweighted, and it is widely known. Perhaps for
this reason, the S&P 500 has becom e an indus­
try benchm ark.26
Assuming there is a special interest in the
S&P 500 as an investment portfolio, w e still
must explain the popularity o f a mutual fund as
a preferred means o f holding that portfolio.
Gorton and Pennacchi (1991) construct an elabo­
rate rationale for security baskets as a way for
uninform ed traders to exploit the inflexibility of
24Vanguard Index Trust (1992), p. 9. For those unfamiliar with
index investments, it is important to note that a buy-andhold investment strategy is incompatible with indexing. The
composition of an index portfolio (i. e., the number of
shares of each stock) depends on the prices of all the
stocks in the index. Therefore, in contrast to a buy-andhold investment, the composition of a theoretically exact in­
dex portfolio changes every time the price of any one of its
component securities changes. A dynamic investment
strategy is required for an index portfolio.
Vanguard is only one of many companies to offer an
S&P 500 index mutual fund for investors. Its use as an ex­
ample should not be interpreted as a recommendation for
or against this or any other mutual fund. There are also
other ways of investing in the S&P 500 index, including in­
dex futures and index options.

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a market index to diversify themselves against
losses to insider trading. A plausible, although
more prosaic, reason is that mutual funds might
be a way to spread the fixed costs o f stock mar­
ket trades over many investors, thus lowering
the average cost faced by each investor. These
costs can be significant. Since stock prices
generally change many times in one day, the
number o f transactions required to maintain a
theoretically exact index portfolio o f 500 stocks
is potentially enormous. As long as there is a
non-zero fixed cost per trade, the sum o f these
fixed costs o f maintaining the index will be
proportionately large.

Redundancy
W e saw in the first case that the prices of
Canadian coinage futures contracts w ere
tracked almost exactly by the prices o f silver fu­
tures; the coinage futures w ere redundant. We
now perform a similar analysis on the index
fund and demonstrate that it too is redundant:
the value o f the fund is closely tracked by the
value o f the index. In this case, however, the
managers o f the fund have actively pursued ex­
actly this correlation as their stated purpose.
Redundancy here helps explain the innovation’s
success.
Figures 5 and 6 are analogous to figures 3
and 4, respectively. Figure 5 plots daily price
observations for the Vanguard 500 Portfolio and
the S&P 500. W e see that the fund price and
the index value move tightly together. Upon
closer examination, the prices seem to be con­
fined to a collection o f line segments radiating
from the origin and rotating dow nw ard as one
moves further out. The line segments are peri­
odically bum ped downward, as maintenance
fees, operating charges and dividend and capital
gains distributions tend to be concentrated in
25See, for example, Fama (1976), chapters 7 and 8.
26There are other commonly used benchmark indexes, for
example, the S&P 100, the Wilshire 5000 Index, or the Dow
Jones Industrial Average.

13

Figure 5

Daily Values for the S&P 500 Index and the
500 Portfolio
Net Asset Value (U.S. $) of the 500 Portfolio

Net Asset Value (U.S. $) o f the 500 Portfolio

S & P 500 Index

Figure 6
Daily Values for the S&P 500 Index and the 500 Portfolio
S&P 500 Index




Net Asset Value of the 500 Portfolio

SEPTEMBER/OCTOBER 1992

14

cumulative year-end adjustments.27 The line seg­
ments also tend to move successively outward
over time, because o f the general upward trend
in stock prices over time. Even with these dis­
continuities, however, a regression o f five-dayholding-period mutual fund returns on S&P 500
returns yields an R2 statistic o f 0.978; according
to the standard measure, the mutual fund is a
nearly perfect hedge for the S&P 500.28
Figure 6 shows the same relationship, but
with the 500 Portfolio values and index values
plotted as time series. Over relatively long peri­
ods o f time, the value o f the index grows at a
slightly higher rate than the value o f the mutual
fund. This long-run discrepancy reflects the fact
that the index is a theoretical portfolio — one
that assumes transaction costs are zero.29 The
mutual fund, on the other hand, charges each
shareholder a fixed quarterly account mainte­
nance fee, plus operating expense charges equal
to .2 percent o f the value o f the fund over the
course o f each year. Over time, these fees ac­
cumulate and com pound to produce a dis­
crepancy.

Performance o f the Security
W e turn now to the question o f the innova­
tion’s success. For this, w e need a measure. The
innovator in this case was the fund’s manager,
the Vanguard Group. W e therefore define a
success as an innovation that profits them. For
an index fund, unlike many other form s o f in­
termediation, the manager profits only through^
its fees. The fund receives periodic fees from its
shareholders, while incurring the costs o f fund
management: accounting, buying and selling
stocks, receiving and disbursing payments, etc.
Data on management costs w ere unavailable,

27Because of differences in the way the index and the mutu­
al fund account for dividends and capital gains, tracking
the net asset value of the mutual fund tends to understate
its performance relative to the index. In particular, the in­
dex generally assumes that dividends, stock splits, etc., are
reinvested, adjusting the index accordingly, while the mutu­
al fund gives investors the option of collecting their divi­
dends and capital gains. Unfortunately, sufficient
information was not available to make accurate compensat­
ing adjustments to the net asset values of the fund.
“ Performing the same analysis with daily returns, the R2
statistic is 0.859. The drop in significance is attributable to
the fact that returns for one-day holding periods are
smaller than for five-day holding periods, relative to noise
factors such as rounding errors.
29As noted in footnote 27, the mutual fund time series
presented here tends to understate its performance relative
to the index. If we were able to compensate for disburse­

Digitized forFEDERAL
FRASER RESERVE BANK OF ST. LOUIS


however, so that profits could not be measured
directly.
Instead, we assume that the fund’s profits are
increasing with revenues over the entire range
considered here. Under this assumption, profits
increase with the size o f the fund. W e there­
fore use the size o f the fund as our measure of
success.30 Figure 7 shows the size o f the fund
both nominally and in constant (CPI-adjusted)
1983 dollars. Almost since its inception in 1976,
the value o f the fund has grow n exponentially.
In nominal terms, the fund currently contains
$4,346 billion, or $3,176 billion in constant 1983
dollars.
One plausible explanation o f the success of an
index mutual fund is transaction costs. Like
many expenses, the cost to an individual inves­
tor o f a stock purchase can be divided into a
variable and a fixed portion: price per share
times number o f shares plus a brokerage com ­
mission. If large numbers o f investors wish to
hold the index, and if the size o f a brokerage
commission is fixed, or at least insensitive to the
quantity transacted, then the investors can pool
their transactions to reduce the total amount of
commissions paid. A mutual fund is one way to
achieve this pooling o f investments.
Although the mutual fund falls short o f the
index in the long run, the relevant comparison
is not with a theoretical entity, but with those
alternatives that are available on a practical ba­
sis. While everyone acknowledges the presence
o f transaction costs, some might argue that these
costs are too small in modern financial markets
to make a difference. Gorton and Pennacchi, for
example, suggest that “investors can costlessly
replicate [these composite securities].”31

ments, the compensated mutual fund price path would lie
above the net asset values shown here, but still below the
curve for the S&P 500. The average annual return calculat­
ed for the mutual fund on a compensated basis was 13.9
percent over the period 8/31/76 to 12/31/91, compared with
14.4 percent for the index. See Vanguard Index Trust
(1992), p. 16.
30A full discussion of the relationship between the size of the
fund and Vanguard’s profits, and therefore of Vanguard’s
incentives to innovate, would require consideration of is­
sues of returns to scale and market structure that are be­
yond the scope of this paper.
31Gorton and Pennacchi (1991), p. i. They go on to state (p. 2)
that “ the popularity of such composite securities seems
puzzling since consumers, on their own, can apparently
accomplish the same resulting cash flow by holding a
diversified portfolio of the same securities in the same
proportions.”

15

Figure 7

Size of the 500 Portfolio
Billions of dollars

Billions of dollars

To demonstrate the potential role o f low er
transaction costs in the success o f the mutual
fund, consider the perform ance o f an index
portfolio managed directly by an individual in­
vestor trading through a brokerage house and
facing realistic brokerage commissions. To make
this example plausible, w e consider pre-tax
returns on an S&.P 500 portfolio for an investor
making a modest number o f trades each day
and able to transact at standard brokerage com ­
mission rates. In particular, w e consider an ini­
tial net investment o f $1 million in the S&P 500
index made on September 1, 1976. Assume that
our investor is able to track the index (approxi­
mately) by making 10 trades per day at an aver­
age cost o f $30 per trade.32 Brokerage commis­
sions on this portfolio thus absorb $300 per
day.

o f the fund. The results are straightforward:
over the course o f almost 15 years, the value of
the index held directly has fallen to about
$860,000 in nominal terms, while the mutual
fund has posted a 119.2 percent gain. If w e
w ere to adjust for inflation and dividends, the
poor perform ance o f the direct portfolio would
be even m ore striking. The result is that inves­
tors w ho would otherwise have to trade at stan­
dard brokerage rates can hold the index more
cheaply as a mutual fund. Indeed, given such
transaction costs, it appears likely that an index
portfolio managed by an individual investor
would have negative e?c ante returns. If this
w ere the cheapest means o f doing so, no one
would want to hold an indexed portfolio.

Figure 8 compares the results for this portfo­
lio with those for the mutual fund over the life

The foregoing has presented tw o case studies
of financial innovations. One innovation, Canadi-

32Brokerage commission schedules are complex and vary
considerably from one broker to another. Some of the fac­
tors that can affect the commission on a trade are volume
discounts, odd-lot trading premia, and negotiated commis­
sions for very active customers. The average $30 fee used

here is based on a commission rate of 1 percent of the to­
tal price of each transaction, an average share price of $30
per share, and trading in single round lots of 100 shares.




CONCLUSIONS

SEPTEMBER/OCTOBER 1992

16

Figure 8
An Index Portfolio Subject to Transaction Costs
Direct Portfolio Value (Millions of dollars)

an silver coin futures, failed. The other, a mar­
ket index mutual fund, has succeeded. Together,
the tw o case studies represent an experiment of
sorts. W e have examined tw o innovations with
a com m on feature: Both w ere redundant in the
technical sense that their price movements were
closely tracked by the price movements o f other
securities. One might say that the first failed b e­
cause it was redundant, while the latter has
succeeded for the same reason.
This conclusion is m ore compelling if w e state
it as the following m ore general proposition:
Given tw o securities with redundant prices (that
is, tw o that are perfect hedges for one another),
investors will be drawn to the one with the
low er transaction and liquidity costs. If there is
no investor clientele for which a redundant
security is the cheaper to employ, then that
security will fail.
W hen stated in these terms, the conclusion
seems obvious. Nonetheless, this proposition is
not universally observed. It requires an explicit
acknowledgement o f the fact that transaction
and liquidity costs can be significant factors in
the financial marketplace. This runs contrary to

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Net Asset Value of the 500 Portfolio

the com m on assumption in financial economics
that capital markets are “perfect,” which im­
plies, among other things, that transaction costs
are zero. While such an assumption may be ap­
propriate in certain applications, a full under­
standing o f the behavior o f financial markets
and innovations requires an appreciation o f
these various hindrances to exchange. Thus, to
the extent that financial frictions such as trans­
action and liquidity costs represent real resource
drains on an econom y, successful financial inno­
vations should normally be regarded as welfareenhancing. By replacing cum bersom e or ineffi­
cient modes o f exchange, successful innovations
can make everyone involved better off.

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American Bankers Association. “ Facts About the New U. S.
Coins,” (ABA, 1965).

17

Black, Deborah G. “ Success and Failure of Futures Con­
tracts: Theory and Empirical Evidence,” Monograph Series
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cember 1970), p. 942.

Johnston, Elizabeth Tashjian, and John J. McConnell “ Re­
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Kane, Edward J. “ Good Intentions and Unintended Evil: The
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Chen, Andrew H., and John W. Kensinger. “ Creating Contin­
gent Liabilities: Master Craftsmanship in Financial En­
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Logue, Dennis E. “ Market-Making and the Assessment of
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Ederington, Louis H. “ The Hedging Performance of the New
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Gorton, Gary, and George Pennacchi. “ Security Baskets and
Index-Linked Securities,” NBER working paper No. 3711
(May 1991).
International Monetary Market of the Chicago Mercantile Ex­
change, Inc. A Guide to Silver Coin Futures Trading (IMM,
1973a).

Miller, Merton H. “ Financial Innovation: The Last Twenty
Years and the Next,” Journal of Financial and Quantitative
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_______ Financial Innovations and Market Volatility (Basil
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SEPTEMBER/OCTOBER 1992

18

Kevin L. Kliesen and John A. Tuttun
Kevin L. Kliesen is an economist and John A. Tatom is an
assistant vice president at the Federal Reserve Bank of
St. Louis. James P. Kelley provided research assistance. This
article was written while Tatom was a visiting economist at
the Austrian National Bank. Tatom received useful comments
in seminars on this paper at the Bank of the Netherlands,
the Swiss National Bank and the Institute of Advanced
Studies in Vienna.

The Recent Credit Crunch:
The Neglected Dimensions
C
o n v e n t io n a l w i s d o m h a s i t t h a t a
credit crunch occurred in the U.S. econom y in
1990-92, causing, or at least contributing to, the
latest recession and jeopardizing the strength of
the recovery. M uch has been written about the
causes and consequences o f the credit crunch
and about remedies for it.1

behavior o f interest rates, interest rate spreads
and commercial bank business loans. This paper
suggests that recent movements in short-term
interest rates and changes in relevant interest
rate spreads cast doubt upon the conventional
credit crunch view.

While the term is widely used, the precise
definition o f a credit crunch is not widely agreed
upon. Credit crunches have in comm on, however,
a slowing in the growth o f—or an outright decline
in—the quantity o f credit outstanding, especially
business loans at commercial banks. Analysts w ho
espouse the credit crunch theory typically have
a more specific definition in mind. In their view, a
credit crunch arises from a reduction in the
supply o f credit. Accordingly, this article uses the
term "credit crunch” to refer only to a reduction
in the supply o f credit. It addresses the credit
crunch hypothesis by examining the existence
and implications o f competing potential sources
of a decline in credit, including the recent

W H A T IS A CREDIT CRUNCH?

’ The Chairman of the Federal Reserve System, Alan Greenspan,
has expressed concern over the slowing in credit growth and
the extent to which it was induced by bank regulators’
attempts to raise bank capital. See Greenspan (1991). Other
Federal Reserve officials who have expressed concern over
the credit crunch during this period include LaWare (1991),
Forrestal (1991) and Syron (1991). Concern over a potential
global credit crunch has been raised by the Bank for
International Settlements (1991) and Japan’s Economic
Planning Agency [see Reuters (1991a)]. Concern for a
national crunch has also surfaced in France [see Reuters
(1991b)]. Also see O’Brien and Browne (1992).

FEDERAL RESERVE BANK OF ST. LOUIS


The traditional notion o f a credit crunch originally
involved the process known as disintermediation—
a decline in savings-type deposits at banks and
savings and loans that result in a decline in
bank lending.2 Episodes o f disintermediation
occurred w hen market interest rates, especially
rates on Treasury bills and commercial paper,
rose above Regulation Q interest rate ceilings at
these financial institutions. As this occurred,
depositors withdrew their funds from banks
and savings and loans to invest at higher open
market rates, and bank credit, especially for
business loans, fell.
2See Kaufman (1991) for a discussion of the origin of this term
in his work with Sidney Homer and for a brief sketch of the
history of credit crunches. For detailed analysis of previous
credit crunches, see Wojnilower (1980).

19

The phrase "credit crunch” was coined in
mid-1966 when the Federal Reserve’s monetary
policy becam e more restrictive; the Fed wanted
to slow the growth o f demand for goods and
services in order to fight inflation.3 In 1966, the
Fed’s actions to slow the growth o f money and
credit were reinforced by allowing short-term
interest rates to rise above the Regulation Q
ceiling rate on bank deposits. As a result,
depositors withdrew their funds from regulated
deposits to seek higher market rates. The reduction
in bank deposits, in turn, limited banks’ ability
to lend and their supply o f credit. What made
this event significant was the Fed's refusal to
accommodate the rise in short-term market
interest rates by raising the Regulation Q ceiling
rates at banks and savings and loans, as it had
done in the past.4 Since financial deregulation
in the early 1980s ended interest rate ceilings,
such regulatory-induced disintermediation can
no longer occur.
A more encompassing view o f a credit crunch
is based on any non-price constraint on bank
lending, not simply on disintermediation. In its
recent application, the source o f this constraint
has presumably been the response by bankers
to increased regulatory oversight and their own
reaction to recent deterioration o f bank asset
values and profitability. Increased savings and
loan failures, as well as increased capital require­
ments, may also have played a part.5
This broader definition o f a credit crunch has
been summarized by the Council o f Economic
Advisers (1992):
A credit crunch occurs when the supply of
credit is restricted below the range usually
identified with prevailing market interest rates
and the profitability of investment projects, (p. 46)
3As a result of this policy action, interest rates rose and credit
became more scarce. For example, in the third quarter of
1966, the interest rate on three-month Treasury bills rose
above 5 percent for the first time in more than 30 years; the
5.04 percent average rate during the quarter was up sharply
from the 4.59 percent rate in the previous quarter. The growth
of the money stock (M1) had already slowed from a 7.3 percent
annual rate in the two quarters ending in the first quarter of
1966 to a 4.3 percent rate in the second quarter of 1966.
This was followed by a decline at a 1.2 percent rate in the
third quarter and a 1.2 percent rate of increase in the last
quarter of 1966. See Burger (1969) and Gilbert (1986) for
discussions of this episode.
4According to Burger (1969), p. 24, the Fed previously accom­
modated the rise in rates in July 1963, November 1964 and
December 1965 by raising the Regulation Q ceiling. This
behavior is also discussed by Wojnilower (1980). One flaw
with the disintermediation view is that a decline in intermedi­
ation through banks does not reduce the total supply of



A credit crunch, either through disintermediation,
overzealous regulators or banks' unwillingness
to lend for some other reason, is therefore
usually thought o f as a supply phenomenon.
The flow o f credit, however, results from the
interaction o f both credit supply and credit
demand. In other words, while supply consider­
ations could certainly result in a decline in credit
flows, a reduction in the demand for credit could
produce the same result. Fortunately, econom ic
theory indicates a criterion for assessing which
o f these is the dominant source o f a change in
the quantity o f credit.

CREDIT CRUNCHES: TH EO RY AND
EVIDENCE
Figures la and lb illustrate the typical analysis o f
the credit market aspects o f a credit crunch using
the supply and demand framework for credit flows.
In this framework, the quantity o f credit
demanded varies inversely with the cost o f credit—
that is, the interest rate—given other factors that
influence overall demand for credit. Conversely,
the quantity supplied o f credit increases with
the interest rate, given the other factors that
influence credit supply decisions.6 We will examine
two scenarios. The first illustrates the credit crunch
hypothesis, namely a reduction in the quantity
o f credit supplied resulting from reduced bank
willingness to lend. The second scenario offers
an alternative. In this case, a reduction in the
demand for bank credit occurs. As will be
explained below, this could be the result o f a
decline in business demand for credit associated
with a reduction in inventory investment.7
C ase I: S u p p ly -in d u c e d d e c lin e in c r e d it .
In figure la, an equilibrium in the credit market
credit unless some of the funds removed from banks are not
tunneled into other credit instruments like Treasury bills or
commercial paper.
5The latter idea is closely associated with Syron (1991), who
has termed the reduction in lending as a ‘‘capital crunch.”
Greenspan (1991) has also supported elements of this
argument, as has the Council of Economic Advisers (1992).
Also see Bernanke and Lown (1991) for a different
perspective on this hypothesis.
6Figures 1a and 1b are drawn conditionally on an expected rate
of inflation. That is, the standard assumption that expected
inflation is not a cyclical phenomenon during business reces­
sions is employed. Therefore, in this framework, a change in
a nominal variable is also a change in a real variable.
7Figures 1a and 1b are not meant to imply that bank credit
determines the level of economic activity. For alternative
explanations about the linkage between bank credit and
economic activity, see the shaded insert on p. 24.

SEPTEMBER/OCTOBER 1992

20

Figure 1a
Decline in the Supply of Credit
Case I: Reduced willingness to lend
Interest Rate

Figure 1b
Decline in the Demand for Credit
Case II: Reduced loan demand by businesses
Interest Rate


FEDERAL RESERVE BANK OF ST. LOUIS


21

Figure 2
Quarterly Change in Domestic Nonfinancial Debt as
a Percent of GDP
Percent

Percent
r7

7 -i

i

1960

62

i

i

64

i

i

66

i

i

68

i

70

72

74

76

78

80

82

84

86

88

90

1992

Periods of business recession are indicated by the shaded areas.

exists at interest rate i0 with a flow o f credit equal
to C0. If one of the other factors influencing the
supply o f credit shifts—for example, if there is a
reduced willingness on the part o f banks to
supply credit at a given interest rate—then the
initial supply schedule (S0) will shift leftward to
Sr As a result, the market interest rate will rise
to i, to eliminate the shortage o f credit and thus
the quantity o f credit will fall to Cr
Case II: Dem and-induced decline in
credit. The quantity o f credit can also fall
because the demand for bank credit declines.
This is shown in figure lb. As before, the
quantity supplied and quantity demanded for
credit are initially in equilibrium at C0 and i0.
As the demand for credit falls, an excess supply
o f credit develops. Accordingly, the interest rate
will decline to a new equilibrium level (ij)—the
8lt is possible for a reduction in the supply of credit to occur
in conjunction with a decline in the interest rate, but this still
requires that the demand for credit declines (shifts to the
left) by more than the supply of credit. Thus, the dominant



point where quantity demanded and quantity
supplied are once again equated.8

Evidence: Credit Flows
The central feature o f a credit crunch—a decline
in the growth o f credit—has occurred in every
period that has been identified as a credit crunch.
Such periods also tend to be recessions. For
example, Kaufman (1991) cites credit crunches
that occurred in 1959, 1969-70, the mid-1970s,
1981-82 and 1990-91. Except for the first, these
periods correspond to each o f the recessions
that have occurred since the late 1950s. The first
instance, in 1959, preceded the only other recession
since then, the recession from 11/1960 to 1/1961.
Figure 2 shows two measures o f the flow of
credit, namely the quarter-to-quarter change in
impulse accounting for the decline in the quantity of credit
would remain the shift in demand. Proponents of the credit
crunch view, however, emphasize the supply channel as the
principle source of the reduction in credit.

SEPTEMBER/OCTOBER 1992

22

Figure 3
Short- and Long-Term Interest Rates
Percent

Quarterly Data

Percent

Periods of business recession are indicated by the shaded areas.

private domestic nonfinancial debt (excluding
federal debt) and the change in total domestic
nonfinancial debt—both expressed as a percent
o f gross domestic product (GDP). Typically, in
recessions, the rate o f debt accumulation declines
relative to GDP.9 This reflects the fact that credit
growth tends to be cyclical, especially the growth
o f private credit; typically, credit growth slows
relative to GDP during recessions and rises
during expansions.10 Thus, it is not possible to
ascertain from figure 2 whether the decline in
credit in each instance caused the recession or
9 The cyclical behavior of public sector deficits and overall
credit demand and its implication for interest rates is
discussed in more detail in Tatom (1984 and 1985).
' “Another factor influencing the private demand for credit,
particularly business credit, is business’ use of internally
generated funds to finance investment. The significance of
the cyclical behavior of these funds is developed by Gilbert
and Ott (1985). Internal funds include retained earnings and
depreciation allowances. When a firm’s investment exceeds
its internally supplied funds, it must turn to external
financing to bridge this gap. Conversely, when internal
funds exceed investment flows, a firm does not necessarily

FEDERAL RESERVE BANK OF ST. LOUIS


was merely a reflection o f the recession.
To determine that, one must look at interest
rate movements over the business cycle.

Evidence: Interest Rate Movements
The two scenarios shown in figure 1 provide
us with a stark contrast: In figure la, the decline
in credit results in a rise in the interest rate, while
in figure lb, the decline in credit is associated
with a decline in the interest rate. A rise in
interest rates, however, is not typical in reces­
sions. Figure 3 shows a long-term interest rate
require external financing. For nonfinancial corporations, the
ratio of fixed investment (plant and equipment) and inventory
investment to internal funds is greater than one during
cyclical expansions, but usually falls below one during
recessions, exhibiting the same cyclical nature of credit
demand. During the seven recessionary periods from 1953
to 1982, the average ratio fell from 1.24 at the business
cycle peak to 1.01 at its trough. A similar pattern developed
in the most recent recession. In the third quarter of 1990,
this ratio stood at 1.15; by the second quarter of 1991, it had
fallen to 0.89. Thus, internal funds were relatively more
abundant for financing investment, so less external financing,
including bank credit, was demanded.

23

Table 1
The Federal Funds Rate and the Business Cycle____________
__________ Federal Funds Rates (percent)__________
A t b u s in e s s
cycle p e a k/
tro u g h

A t c lo s e s t p e a k 1

A t c lo s e s t tro u g h 1

111/1957-11/1958

3.24 / 0.94

SAME

SAME

11/1960-1/1961

3.70 / 2.00

3.99 (-2 )

1.68 (+2)

IV/1969-IV/1970

8.94 / 5.57

8.98 (-1)

3.86 (+1)

IV/1973-1/1975

10.00 / 6.30

10.57 (-1)

5.41 (+1)

1/1980-111/1980

15.07 / 9.83

SAME

111/1981-IV/1982

17.59 / 9.28

17.79 (-1)

8.66 (+1)

111/1990-11/1991

8.16 / 5.86

9.73 (-5 )

3.77 (+4)2

B u sin e ss cycle
p e a k /tro u g h

SAME

'The number o< quarters earlier ( - ) or later (+) in which the closest federal funds rate peak or
trough occurs is indicated in parentheses.
2Latest data available.

(the yield on long-term government bonds) and
a short-term interest rate (three-month Treasury
bills) since 1947. Typically, both long- and short­
term interest rates decline during recessions,
although the long-term rate is much less cyclical
than the short-term rate. Indeed, short-term
interest rates sometimes reach a peak before the
business cycle peak. In the latest instance, in
particular, the three-month Treasury bill rate
peaked at 8.54 percent in the first quarter o f 1989,
six quarters before the business cycle peak.

since credit crunches are allegedly the result of
Federal Reserve policy actions to reduce credit
availability, the interest rate in the federal funds
market may be a more useful indicator.
Table 1 shows the average federal funds rate
at the business cycle peak and trough and the
nearest peak and trough o f the rate itself. The
fed funds rate typically peaks before or at the
business cycle peak, suggesting that the type of
supply shift shown in figure la does not occur
during recessions. Like the three-month Treas­
ury bill rate, the fed funds rate typically falls
before and during recessions.

An alternative measure of short-term interest
rate movements is the interest rate in the
federal funds market. Briefly, the fed funds
market is the market in which banks compete
daily for excess reserves to meet their level of
required reserves. Since the fed funds market is
heavily influenced by Federal Reserve policy
actions (through open market operations), some
analysts believe that the behavior o f this key
short-term rate can provide direction about the
relative tightness o f bank credit.11 Accordingly,

There are periods, o f course, when short-term
interest rates rise and the flow o f credit declines.
Figures 2 and 3 support the earlier discussion
which indicated that such developments occurred
in 1966 and, to a certain extent, over stretches
during the period 1986-88. Interest rates and
the demand for credit, however, tend to be pro­
cyclical, both when the econom y is in recession

"Since the Fed and banks create money largely by acquiring
debt instruments (loans and investments in debt issued
by governments, firms and individuals), analysts typically
use the terms money and credit interchangeably. Some
analysts, like Kaufman, regard the principal channel of
influence of monetary policy to be its effect on credit, not
on the money stock or other measures of monetary assets.
Kahn (1991) suggests that the linkage between bank loans
and monetary aggregates is weak, so that a slowing in
monetary growth could not have caused bank loan growth

to fall in 1990 nor could an increase in money growth have
raised bank lending. Walsh (1991) argues that the recent
credit crunch reflects a decline in the demand for credit,
not in its supply, and that traditional monetary policy
actions can change the supply of credit independently
of bankers’ willingness to make loans. Some analysts look
at the excess reserve holdings of commercial banks as
an indicator of a credit crunch, but Haubrich (1991)
finds this measure an unreliable indicator of credit
conditions.




SEPTEMBER/OCTOBER 1992

24

Bank C redit and E co n o m ic A ctivity
Many analysts attribute a central, causal
role in business cycle developments to bank
credit movements, regardless o f the reasons
for such movements. For example, some re­
searchers suggest that it is the interplay of
credit and real econom ic activity that pro­
vides banks and monetary institutions with a
potentially direct role in business cycle develop­
ments.1 In particular, they view the growth o f
the m oney stock as purely passive, responding
to the general movements o f the economy,
while disruptions to credit markets have real
consequences for output and employment
decisions. Thus, in this view, a decline in
credit supply is critically important in causing
and maintaining recessionary conditions.2
A related view assigns a special role to
banks in extending credit and promoting
econom ic activity. This view emphasizes that
many firms are relatively small and have
limited access to organized financial markets
(for example, the commercial paper market).
Accordingly, these firms’ ability to expand is
constrained by their access to bank credit.3
The special role o f banks, then, is to provide
objective evaluations and monitoring services
for the continuing viability and credit worthiness
o f this relatively large sector o f the economy.
Thus, one dollar o f bank credit is not a
perfect substitute for one dollar o f other
credit, like a direct personal loan or the
proceeds from selling commercial paper.

’ This is known as the “ credit view” of the transmission
mechanism. Gertler (1988) reviews the literature on the effects
of credit market shocks. See also Gertler and Hubbard (1988)
and Bernanke (1986). Bernanke (1983) and Hamilton (1987)
argue for an independent role of credit in explaining the
Great Depression. The credit view is an extension of the
approach taken by real business cycle (RBC) researchers.
See, for example, Plosser (1991).
2Analyses of the unique role of bank credit sometimes focus
on changes arising from changes in reserve requirements.
Since reserve requirement changes affect bank credit,
given deposits, it is easy to infer that bank credit can
change independently of movements in money. Such
analyses ignore the role of the Federal Reserve. A change
in bank credit because of a change in reserve require­
ments, however, results in an equal and offsetting change
in credit supplied by Federal Reserve Banks, as the Fed
accommodates the change in demand for required reserves
available by buying or selling securities or other assets.
Accordingly, there is no change in the net total of credit
associated with a given money stock and adjusted


FEDERAL RESERVE BANK OF ST. LOUIS


Bank credit carries with it the banker’s
certification o f credit-worthiness and the
banker’s implicit contract for future moni­
toring services, the provision o f financial
advising and other financial services.
Furthermore, extensions o f bank credit to
firms provide information to potential
customers, financiers and other suppliers
about the firm’s econom ic prospects. In
this view, not only does the supply o f cred­
it play a unique role, independent of
monetary policy developments, but bank
credit is also the principal linchpin for the
influence o f financial market developments
on real econom ic activity
Whether a slowing in the growth o f business
loans is considered a source o f recessionary
pressures on econom ic activity or simply a
reflection o f the recession is important to
both business cycle analysts and policymakers.
If the supply o f credit plays a central role
and is not simply a reflection o f monetary
aggregate movements, then policymakers may
need tools to operate specifically on the
credit supply. If credit movements do not
change independently or exert an indepen­
dent influence, however, traditional monetary
policies—namely, open market operations—
can reliably address cyclical problems;
credit market conditions will provide
no more than useful supporting
information.

monetary base. Thus, movements in credit or money
during such episodes are not especially unique
compared with those in periods when reserve
requirements do not change.
3A related argument stresses segmented markets, so that
relatively small firms have no access to organized capital
markets. Blinder and Stiglitz (1983) discuss the
independent function of bank loans. James (1987)
provides evidence supporting the view that bank loan
extensions raise the value of firms. Judd and Scadding
(1981) were the first analysts to model an independent
role for bank loans to cause changes in the money stock.
See Anderson and Rasche (1982), however, for a critical
discussion of their model. More recently, analysts have
focused on the structure of loan contracts and on loan
commitments as a mechanism for avoiding credit
rationing. See Duca and VanHoose (1990) for a model of
the effects of loan commitments on optimal monetary
policy.

25
/

and when it is not.12 In the latest instance, in
fact, interest rates and credit flows were declining
well before the econom y entered the recession.
Thus, the evidence presented in this section is
consistent with the hypothesis that, during
episodes that have been characterized as credit
crunches, the factors that affect the demand for
credit tend to outweigh any possible effects
from factors influencing the supply o f credit.13
The appropriate interpretation o f credit market
developments during the latest "credit crunch” is
that illustrated in figure lb.

should rise relative to the interest rate at which
they borrow (deposits). This is a poor test, how ­
ever, because periods when credit crunches are
believed to occur also tend to be periods of
recessions, w hen the bankruptcy rate and
default rates on business loans rise. Thus, the
spread between a bank’s lending and borrowing
rates should rise to compensate for these risks.
Therefore, while interest rate spreads cannot
provide definitive support for the existence o f
a credit crunch, they can provide some evidence
about the comparability o f the most recent episode
by comparing the recent spreads with earlier ones.

CO R R O B O R ATIN G EVIDENCE:
INTEREST RATE SPREADS

Figure 4 shows the quarterly interest rate spreads
for some relatively risky short- and long-term
securities from 1947 to the present. The short­
term spread measures the prime rate relative to
the interest rate on three-month Treasury bills,
while the long-term spread is the excess o f
riskier BAA bond yields over AAA bond yields.15
Thus, a rise in the spread indicates an increase
in risk.

Economists have long pointed to the informational
content o f interest rate spreads for econom ic
activity.14 This observation stems from the fact
that certain credit market instruments have similar
characteristics and are more or less substitutable.
Thus, if the interest rate on one instrument
changes relative to its substitute, this may provide
information about the behavior o f credit market
participants. For example, evidence o f unusual
bank lending behavior might be obtained by
looking at the difference between bank lending
rates and the rates banks pay for deposits or
between rates available at banks and those avail­
able elsewhere.
This "pricing” behavior o f banks has a direct
application in examining credit market conditions.
If banks becom e more reluctant to lend, then
the interest rate at which they lend (bank loans)
12As pointed out by Gilbert (1976), one must distinguish
between the demand for long-term credit and the demand
for short-term credit when discussing the cyclical nature of
credit demand. The demand for certain types of long-term
credit tends to increase toward the end of a recession. (For
example, many firms undertake bond and equity financing
to lengthen the maturity of their capital structure). This rise
reflects a shift away from short-term credit and not a rise in
total credit demand. In effect, firms not only reduce credit
demand, they also restructure their financing, shifting toward
longer-term financing like bonds and especially new equity.
13Schreft (1990) discusses the role of credit policy in the 1980
recession. In this case, however, a rise in money demand,
especially in its currency component, contributed to cyclical
developments; for example, see Tatom (1981). Another recent
example of a credit crunch that differs from the stereotype
discussed here is the effect on world credit markets of the
economic reformation of the Eastern and Central European
economies. In this instance, a rise in their demand for capital
™ expected to raise the total demand and the real rate of
interest in world credit markets. While an excess demand
for credit will initially occur, and the interest rate is expected
to rise, the total quantity of credit does not fall. See the Bank
for International Settlements (1991) for a discussion of this
credit crunch, although they do not refer to the situation as



During recession periods, the spread on risky
assets rises, especially the short-term spread,
because—as figure 4 shows—that is where most
o f the risk is. The rise in rates banks charge on
loans that are inherently more risky in recessions—
relative to their costs on insured deposits—need
not reflect a new reluctance to lend beyond that
arising from recession risk. Compared with the
rise in spreads (on risky assets) in previous
recessions, however, the recent spreads did not
rise unusually. In fact, the long-term spread
actually fell in 1991 before the recession ended.
a credit crunch and they emphasize the effects of an earlier
decline in world saving in their analysis. Also see Sesit (1991)
for some doubts concerning this analysis. The Council of
Economic Advisers (1991) argues that real interest rates
were boosted by European developments in late 1990. Such
a shift in the overall demand for credit and rise in the real
interest rate would be expected to create the usual credit
crunch conditions in other economies as credit is diverted
to Eastern Europe. This argument has not been raised,
however, in the context of the 1990-91 U.S. credit crunch.
14For example, Brunner and Meltzer (1968) emphasized the
role of credit and asset prices, or interest rate spreads,
in the transmission of monetary policy over the business
cycle. See Bernanke (1990) for a recent study of interest
rate spreads.
15Bernanke (1990) points out that the spread between the
BAA bond rate and the AAA bond rate is a measure of
default risk.

SEPTEMBER/OCTOBER 1992

26

Figure 4
Selected Interest Rate Spreads
Percent

Q uarterly Data

Percent

Long-term spread is the excess of the yield on BAA-rated bonds over AAA-rated bonds.
S hort-term spread is the prim e rate less the yield on 3-m onth Treasury bills.
Periods o f business recession are indicated by the shaded areas.

Moreover, the short-term spread was lower than
in the three previous recessions. While figure 4
shows that the price o f risk rises in recessions,
it provides insufficient evidence o f bank un­
willingness to lend.

o f the risk arising from a recession.16 This spread
rose from 196 basis points in III/1990—w hen the
recession started—to about 265 basis points at
the end o f the recession; it rose slightly more in
the fourth quarter o f 1991.

Although bank willingness to lend is certainly
a function o f default risk, a bank’s demand for
funds to intermediate is also a factor. Figure 5
shows the spread between banks’ lending and
borrow ing rates, where the prime rate is the
lending rate and the interest rate paid on large
negotiable certificates o f deposit (CD) is used for
the bank borrowing rate. A rise in this spread
could reflect an increased reluctance to lend like
that envisioned by credit crunch analysts, but
this reluctance may simply reflect an assessment

The rise in the spread and its recent levels,
however, are both smaller than the peak spreads
observed in the 1980 and 1981-82 recessions.17
While the spread in 1990-91 was higher than in
the 1969-70 and 1973-75 recessions, the rise in
the spread during each o f the four previous
recessions was larger than the rise during the
most recent recession. Therefore, if an increase
in the spread between the prime rate and the
CD rate is associated with an increased unwill-

16There is a distinct negative relationship between the prime
rate and CD rate spread in figure 5 and the growth rate of
C&l loans over the (available) sample period 1/1970 to
11/1992. The correlation between these two measures is
-0.43, which is statistically significant at the 1 percent level.

17The difference between movements in inflationary expectations
in the most recent recession and in the previous recessions
may explain part of the difference. Changes in inflationary
expectations, however, should affect both interest rates in
the same direction.


FEDERAL RESERVE BANK OF ST. LOUIS


27

Figure 5
Spread Between the Prime Rate and the Rate on
3-Month Certificates of Deposit
Percent

Quarterly Data

Percent

Periods of business recession are indicated by the shaded areas.

ingness to lend, then in the most recent case
such unwillingness was smaller than usual.18
Another related measure that could indicate a
rise in bankers’ reluctance to lend is the spread
on banks' borrow ing rates com pared to rates
available to lenders elsewhere. Figure 6 shows
how bank borrow ing rates change relative to
other safe, short-term rates during recessions.
Because the intermediation process occurs
through the initial issuance o f bank liabilities
(that is, a bank attracts deposits that it will then
relend), a bank’s demand for funds to intermediate
should show up in the CD rate.
>8lt is possible that the spread for some borrowers, or in
some sectors or regions, rose unusually in this recession,
perhaps reflecting some risk beyond those typically
associated with recessions.
19See Gilbert (1976) for a discussion of the earlier episode and
the typical weakness of loan demand early in a recovery.
20Figure 6 also shows that the rate on CDs generally increases
at some point early in a recession. This rise probably occurs



Figure 6 shows that the spread between the
three-month CD rate and the three-month
Treasury bill, although somewhat volatile, always
declines from peak to trough. Furthermore, this
spread typically falls sharply late in recessions
and for a while thereafter. For example, this spread
fell through most o f 1970, at the beginning and
end o f the 1973-75 recession, at the trough in
1980 and during much o f the 1981-82 recession.19
Generally, however, this spread appears to be
relatively higher at some point in each recession
than it was at the business cycle peak.20 Following
a brief surge in the fourth quarter o f 1990, the
CD rate declined at the end o f the recession and
because of the perceived riskiness of CDs due to bank failure;
however, since the “ too-big-to-fail” doctrine, and especially
since the savings and loan bailout, CDs are about as safe
as Treasury bills. Thus, this spread— as shown in figure
6— had moved to relatively low levels even before the latest
recession. The decline in the spread immediately before the
recession is consistent with an earlier decline in bank loan
growth.

SEPTEMBER/OCTOBER 1992

28

Figure 6
Spread Between the Rate on 3-Month Certificates of
Deposit and the Rate on 3-Month Treasury Bills
Percent

Quarterly Data

Percent

“ I— I— I— T T — I— I— I— I— T T - T T — I— I— I— I— 1— I— I— T—
1970 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 1992
Periods o f business recession are indicated by the shaded areas.

early in the recovery—just as it did previously.
By the third quarter o f 1991, the spread between
the CD rate and the Treasury bill rate had fallen to
its lowest level since 1976-77. This narrowing o f the
spread (that is, a relative decline in the CD rate)
and its relatively low level are consistent with
reductions in banks' demand for funds—either
because loan demand was weaker or because
bankers were reluctant to lend. In either case,
however, the recent decline in this spread is
much smaller than the peak-to-trough decline
in the four previous recessions.
The evidence on bank pricing indicates that the
spread between the lending (prime) and borrowing
(CD) rate widened during the recent recession, as it
typically does, although not by as much. It also
indicates that the prime rate rose and the CD rate
fell relative to the Treasury bill rate. The decline
in the latter was not unusual, nor was it unusually
large. Since it is not unusual for bank margins
to rise in recessions or for the CD rate to fall at

FEDERAL RESERVE BANK OF ST. LOUIS


the end o f recessions, these arguments, while
consistent with the credit crunch hypothesis, do
not support the view that bankers have been
less willing to make business loans. The critical
issue in reaching this conclusion is whether
interest rate spreads reacted unusually in the
most recent recession. As shown in figures 4
through 6, they did not.
So far we have focused on the specifics o f a
credit crunch—as hypothesized by a simple
model for the demand and supply o f credit—
and on the evidence from interest rate spreads.
This evidence questions the supply-side argument
behind the credit crunch hypothesis and shows
the recent episode was not unusual relative to
earlier instances when, others have argued, cred­
it crunches occurred. This leaves open the issue
of the source of movement in the demand for
business credit at banks during these periods.
The nexus between the demand for business
loans and business inventories is explored below.

29

COMMERCIAL AND INDUSTRIAL
LOANS: CAUSE FOR CONCERN?

W H Y DOES THE FLOW OF CREDIT
DECLINE IN A RECESSION?

The U.S. econom y officially entered a
recession in the third quarter o f 1990, when
real GDP contracted at a 1.6 percent rate.
Output continued to contract in the fourth
quarter o f 1990 and the first quarter o f 1991,
declining at a 2.9 percent rate over the threequarter period. One o f the factors blamed for
the recession was the unusual weakness o f busi­
ness loans.21 Even after signs o f recovery began
to emerge in the spring and summer o f 1991,
commercial and industrial loans at banks
(hereafter, business loans) remained weak.
For example, nominal commercial bank loans to
business fell from $642.5 billion in the fourth
quarter o f 1990 to $620.7 billion in the fourth
quarter o f 1991, after rising at only a 0.1 percent
rate over the previous year. By the first quarter
o f 1992, business loans fell to $612.8 billion;
they dropped further in the second quarter to
$602.8 billion. As a result, concern about wheth­
er the recession had ended or whether the
econom y would have a double-dip, with real
GDP resuming its earlier decline, continued well
into the winter o f 1991-92.

W hen sales slow, firms have an incentive to
reduce production and employment to avoid an
accumulation o f undesired inventory. Such a
reduction in output and employment constitutes
a typical recession. But firms also alter their
other investment decisions during recessions.
For instance, firms also reduce their demand for
new plant and equipment based on lower
desired output levels and growing excess
capacity. As a result, overall investment and its
financing tend to decline during recessions.

There are at least two reasons why analysts are
concerned about business loan growth. The first
is the concern raised by proponents o f the credit
crunch view o f the recent recession: slow growth
of bank lending could reflect unusual structural
problems in banking.22 Second, slow growth in bus­
iness loans is an indication that business activity
is not expanding. If businesses are reluctant to
expand, the potential for econom ic recovery is
jeopardized. What is absent from the discussion,
however, is the fact that business loans typically
grow more slowly in recessions. This is examined
in greater detail in the next section.
21See the references in footnote 1. For differing analyses, see
Brenner and Schmidt (1991), Corcoran (1992), Furlong (1991)
and Bacon and Wessel (1991), Heinemann (1991), Jordan
(1992), Meltzer (1991), Passell (1991) and Prowse (1991).
Syron (1991) attributes the weakness in bank loans and
economic activity to a shortage of capital induced by higher
capital requirements and bank losses. Parry (1992) argues
that policy-related changes in the real cost of intermediation
have been appropriate, even if they have permanently
changed the extent of bank intermediation.
22The Council of Economic Advisers (1991) discusses several
reasons for the decline in bank credit growth. It notes, how­
ever, that the substitution of other debt should have offset
the decline in bank lending. Strongin (1991) also stresses
that credit reductions have been offset by increased equity
financing. Bernanke and Lown (1991) point to an absence of
business loan growth. They indicate that other sources of
business loans show a decline that is unusually large for



The Decline in Inventory
Investment in Recessions
The role o f inventory investment in recessions
is especially important. Indeed, one principal type
o f recession is called an inventory recession because
o f the central role o f changes in inventories.23
In an inventory recession, an unanticipated decline
in sales growth leads to an undesired build-up
o f inventory followed by adjustments to produc­
tion and employment. As firms reduce inventory
to eliminate the initial excess, inventory investment
becom es negative; however, such investment
must eventually be restored to continue meeting
the slower pace o f expected sales. This eventual
rise in inventory investment implies that some
firms’ production and sales have risen, thereby
setting in motion an overall cyclical expansion.
Thus, an inventory recession is characterized by,
first, an initial rise in inventories relative to
sales (before, or in, the initial stage o f a recession),
second, a subsequent decline in inventory invest­
ment to a negative pace, and finally, a rebound
in inventory investment before or at the
recession’s end.
them during recessions, reinforcing the view that the overall
demand for business loans fell, not the supply. They also
provide evidence that New England banks’ efforts to raise
capital had a relatively small impact on bank lending, although
not necessarily on business loans. Feldstein (1992) argues
that the imposition of risk-based capital standards has re­
stricted banks’ ability to intermediate.
23The cyclical behavior of inventory investment and inventory
recessions are described in more detail in Tatom (1977).
The first effort to formally model the inventory cycle is Metzler
(1941). Blinder and Maccini (1991) provide a recent review of
the state of research on inventories.

SEPTEMBER/OCTOBER 1992

30

Figure 7
Change in Business Inventories
B illio n s o f 1987 d o lla rs

1959

61

63

65

Q u arterly Data

67

69

71

73

75

77

B illio n s o f 1987 d o llars

79

81

83

85

87

89

1991

P eriods o f bu sine ss recession are in dicated by th e shaded areas.

Figure 7 shows the change in inflation-adjusted
business inventories since 1959. Inventory invest­
ment does not always rise unusually at the busi­
ness cycle peaks. Indeed, in half the instances
shown, including the latest, inventory investment
falls at the business cycle peak. Also, it is un­
com m on for inventory investment to register
increases at the end o f a recession or in the
trough quarter. It is not unusual for it to rise in
the first quarter o f the recovery. Such a rise
occurred in seven o f the past eight recessions,
although, in four o f these cases, inventory
investment remained negative in the quarter
following the business cycle trough. Therefore,
while all recessions do not conform to the
stereotypical inventory recession pattern,
there is no question that movements in inventory
investment play a central role in recessions.
The decline in overall investment and real GDP

FEDERAL RESERVE BANK OF ST. LOUIS


in recessions is concentrated most heavily in
their inventory investment component.
Table 2 shows that the decline in the constantdollar change in business inventories accounts
for much o f the business cycle peak-to-trough
decline in real GDP. Excluding the relatively
large swings in inventory investment (as a share
o f the decline in GDP) in the 1960-61 and
1969-70 recessions, the decline in inventory
investment in the most recent recession 44#.2
percent) was fairly typical. It exceeded that in
three o f the previous eight recessions, although
inventory investment already had declined
rather substantially from early in 1989 to the
business cycle peak in III/1990. For the recent
period o f decline in real GDP (11/1990 to 1/1991),
the decline in inventory investment o f 54.6
percent o f the production decline exceeded that
in four o f the previous eight recessions.

31

Table 2
The Decline in Inventory Investment in Recessions
Recession
peak-trough

Change in
real inventory
investment1

Change in real
GDP'

Column 1 as
a percent
of column 2

IV/1948-IV/1949

$-28.3 billion

$-20.9 billion

111/1953-11/1954

-11.1 (-18.4)

-37.4 (-43.3)

29.7 (42.5)

111/1957-11/1958

-20.1 (-22.5)

-44.9 (-53.1)

44.8 (42.4)

11/1960-1/1961

-15.7 (-45.5)

5.7 (-15.8)

-275.4 (288.0)

IV/1969-IV/1970

-22.5 (-19.8)

-1.8 (-25.0)

1250.0 (79.2)

135.4%

IV/1973-1/1975

-84.7

1/1980-111/1980

-44.3 (-10.7)

-97.3 (-98.2)

45.5 (10.9)

111/1981-IV/1982

-80.6 (-35.0)

-104.9 (-110.1)

76.8 (31.8)

111/1990-11/1991

-31.6 (-57.9)

-65.5 (-106.0)

48.2 (54.6)

-135.1

62.7

'Prior to 1960, data are expressed in 1982 dollars. From 1960 to the present, data are in 1987
dollars. Numbers in parentheses correspond to the data for the respective peak-to-trough periods
for real GDP: II/53-II/54, III/57-I/58, I/60-IV/60, III/69-II/70, I/80-II/80, 111/81-111/82 and 11/90-1/91.

The Linkage Between Business
Loans & Business Inventories
Inventory decisions are also central to business
loan behavior during recessions.24 Since banks
tend to hold short-term liabilities, w hich in large
part are payable on demand, they have a strong
incentive to hold relatively short-term loans. Thus,
bank loans and lines o f credit to business are
principally related to business financing o f short­
term assets, such as inventories. Inventory assets
are crucial because they are superior collateral
to receivables. Moreover, the value o f receivables
can disappear more easily than that o f inventory
in the event o f default; inventory also can be
taken over and liquidated more easily.
Figure 8 shows the stock o f business inventories
and business loans since 1959, both measured in
nominal terms.25 Business loans and business
inventories move together over time. For example,
both rise slowly until 1973, then accelerate sharply
until late 1974. At the end o f the 1973-75 recession
and during the early quarters o f the recovery,
business loans declined along with business
24For a textbook treatment of the interplay between business
loans and business inventories, see Goldfeld (1966).
25The business loan series begins in 1959, but is only available
for the last Wednesday of each month until 1973. After 1973,
the data are quarterly averages of Wednesday data. The
stock of business inventory is end-of-quarter data, based on
estimates of the change in business inventory. The value




inventories. The growth rates o f each series
appear to slow in the 1980 recession and at
the end o f the 1981-82 recession. Inventory
growth is unusually slow from early 1982 to
the end o f 1986 compared with loan growth,
however. Over this period, business loans
rose from about 44 percent o f inventories
to about 59 percent, reflecting the slowing in
inventory growth.
Since the end o f 1986, both business loans
and inventories have grown at about the same
rate, keeping business loans at about 60 percent
of inventories. Both measures declined in the
recent recession, following a slowing in growth
in 1989 and 1990. For example, from the first
quarter o f 1987 to the first quarter o f 1989,
business loans rose at a 5.9 percent annual rate,
while business inventories rose at a 7.9 percent
rate. During the same interval, overall nominal
final sales in the U.S. econom y grew at a 7.9
percent rate.26 Over the next six quarters, final
sales growth slowed to a 5.7 percent rate, while
inventory growth slowed to a 4.3 percent rate
and business loans slowed to a 3.0 percent rate
of business inventory typically is much larger than that of
business loans.
26Final sales is the sum of gross private domestic fixed
investment, personal consumption expenditures, net exports
and government purchases. GDP is the sum of final sales
and the change in business inventories.

SEPTEMBER/OCTOBER 1992

32

Figure 8
Business Loans and Business Inventories
B illions of dollars

Quarterly Data

B illions of dollars

Periods o f business recession are indicated by the shaded areas.

o f advance. Finally, during the recent recession,
from the third quarter o f 1990 to the second
quarter o f 1991, final sales growth slowed to a
3.1 percent rate and inventory fell $27.6 billion,
or at a 3.3 percent rate. The decline in business
loans over the recession totaled $11.9 billion—
a 2.5 percent rate o f decline.
The link between nominal business loans and
nominal business inventories is more systematic
than the simple upward trends in figure 8 might
suggest. Quarter-to-quarter changes in business
loans are statistically related to quarter-toquarter changes in the stock o f inventories in a
significant and positive fashion.
Figure 9 shows the change in business inventories
and the change in business loans (both in current
dollars); the two series are expressed as percentages
o f GDP to scale the data, but this has no effect on
the close visual relationship between the two series.
The correlation coefficient for these changes over

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the period II/1959-II/1992 is 0.52, w hich is
statistically significant at the 5 percent level.
Stronger evidence for the relationship between
business loans and business inventories can be
obtained from causality analysis. In simple terms,
causality analysis examines the statistical direction
o f influence from one variable to another; in
particular, it assesses whether there is a statis­
tically significant, temporal sequence between
changes in one measure and another. This issue
is addressed in the appendix. The results there
support the hypothesis that changes in business
loans are significantly influenced by changes in
business inventories. W hen inventory investment
falls, as it does in every recession, it is not
surprising, therefore, to see an accompanied
weakness in commercial bank business loans.

CONCLUSION
The recent decline in the growth o f business
loans at commercial banks reflects normal

33

Figure 9
Quarterly Changes in Business Inventories and
Business Loans (Percent of GDP)
Percent

Percent

Periods o f business recession are indicated by the shaded areas.

cyclical phenomena. While this decline has been
referred to as a credit crunch, it is unlikely to
have occurred because bankers were unusually
reluctant to make business loans, as is sometimes
suggested. Instead, as in earlier credit crunches/
recessions, the decline most likely originated on
the credit demand side.
No doubt there are individual cases in which
supply factors have been important in reducing
credit availability. Indeed, some researchers have
alleged that such occurrences explain, to a small
extent, business loan slowings in some parts of
the country owing to changes in bank
capital requirements or other regulatory changes.
These analyses generally do not control for the
normal cyclical phenomena addressed here,
however.
The decline in business loan growth in recessions
is due, in large part, to the cyclical nature of
business loan demand. Bank loans are typically
short-term collateralized loans, so that the prime
commercial asset that is financed by bank credit



is inventories. The evidence presented here sug­
gests that business loans and business inventory
holdings are very closely related statistically, so
that business loans and inventory move up or
down in tandem. Since businesses typically
reduce their desired inventory holdings during
recessions, business loans at banks tend to
decline as well.
An additional consideration is the recent
movement in interest rates and interest rate
spreads. As in earlier periods o f so-called credit
crunches, the recent decline in business loans
has been accompanied by reductions in interest
rates, particularly short-term rates. This behavior
is inconsistent with a shortage o f credit from a
simple supply and demand perspective. While
interest rate spreads for "risky” credit have risen
recently, including the difference between bank
lending and borrow ing rates, this is also a normal
cyclical phenomenon. This spread, as well as that
between the prime rate and the three-month
Treasury bill rate, have not been unusually large

SEPTEMBER/OCTOBER 1992

34

com pared with previous recessions, nor has their
increase been unusually large. Although the
spread between the large CD rate and three-month
Treasury bill rate has fallen, this too is not un­
usual in a recession nor in the initial stages o f a
recovery.
To summarize, the theory and evidence pre­
sented here suggests that recessions cause in­
ventory demand and the grow th o f business
borrow ing to slow. To the extent that this argu­
ment and evidence characterize recent develop­
ments, the solution to the recent decline in
credit grow th is likely to be found, as usual, in
a restoration o f business inventory accumul­
ation and its financing.

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Duca, John V., and David D. VanHoose. “ Loan Commitments
and Optimal Monetary Policy,” Journal of Money, Credit
and Banking (May 1990), pp. 178-94.
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Wall Street Journal, March 6, 1992.
Forrestal, Robert P. “ Policy Implications of a Credit Crunch,”
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Crunches— Causes and Cures,” Wellington, New Zealand,
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Furlong, Fred. “ Financial Constraints and Bank Credit,” Fed­
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24, 1991).
Gertler, Mark. “ Financial Structure and Aggregate Economic
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Gertler, Mark, and R. Glenn Hubbard. “ Financial Factors in
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Bacon, Kenneth H., and David Wessel. “ Wary Lenders,”
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Gilbert, R. Alton, and Mack Ott. “ Why the Big Rise in Business
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Goldfeld, Stephen M. Commercial Bank Behavior and Economic
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Bernanke, Ben S. “ On the Predictive Power of Interest Rates
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Greenspan, Alan. “ Statements to Congress,” Federal Reserve
Bulletin (May 1991), pp. 300-310.

_______ “ Alternative Explanations of the Money-lncome
Correlation,” Real Business Cycles, Real Exchange Rates
and Actual Policies, Carnegie-Rochester Conference Series
on Public Policy (Autumn 1986), pp. 49-100.

Hamilton, James D. “ Monetary Factors in the Great Depres­
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Haubrich, Joseph G. “ Do Excess Reserves Reveal Credit
Crunches?” Federal Reserve Bank of Cleveland Economic
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Heinemann, H. Eric. “ The ‘Credit Crunch’ Is a Red Herring,”
Christian Science Monitor, October 1, 1991.

Bernanke, Ben S., and Cara S. Lown. “ The Credit Crunch,”
Brookings Papers on Economic Activity (2:1991), pp. 205-47.

James, Christopher. "Some Evidence on the Uniqueness of
Bank Loans,” Journal of Financial Economics (December
1987), pp. 217-35.

Blinder, Alan S., and Louis J. Maccini. “ Taking Stock: A Crit­
ical Assessment of Recent Research on Inventories,” Jour­
nal of Economic Perspectives (Winter 1991), pp. 73-96.
Blinder, Alan S., and Joseph E. Stiglitz. “ Money, Credit Con­
straints, and Economic Activity,” American Economic Re­
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Brenner, Joel Glenn, and Susan Schmidt. “ Bankers Say
There’s No ‘Credit Crunch’,” Washington Post, October 12,
1991.

Jordan, Jerry L. “ The Credit Crunch: A Monetarist’s Per­
spective,” paper presented at the 28th Annual Conference
on Bank Structure and Competition, Federal Reserve Bank
of Chicago, May 7, 1992.
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Brunner, Karl, and Allan H. Meltzer. “ Liquidity Traps for
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Kaufman, Henry. “ Credit Crunches: The Deregulators Were
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Corcoran, Patrick J. “ The Credit Slowdown of 1989-91: The
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LaWare, John P. “ Setting the Global Scene: A Global Credit
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August 15, 1991.

Council of Economic Advisers. Economic Report of the Presi­
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http://fraser.stlouisfed.org/
FEDERAL RESERVE BANK OF ST. LOUIS
Federal Reserve Bank of St. Louis

35

O’Brien, Paul Francis, and Frank Browne. “ A Credit Crunch?
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_______ “ Energy Prices and Short-Run Economic Perform­
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Appendix
Business Loans and Business Inventories:
Some Statistical Evidence
The relationship between inventory decisions
and the growth o f business loans can be exam­
ined using a straightforward causality test,
which tests the statistical significance o f the
temporal sequence between measures that are
hypothesized to be related. The growth rate of
business loans (L = 400 AlnL) and business
inventories (I = 400 Alnl) can be examined to see
(1) whether one measure "causes” the other; (2)
whether they each cause the other (bi-directional
causality) or (3) whether they are statistically

independent.1 This is done by examining the
statistical significance o f past values o f one
measure in explaining the other, controlling for
the time series properties o f the other.
Considered alone, the growth in business
loans (L) and in business inventories (I) are firstand third-order autoregressive series, AR1 and
AR3, respectively, w hich means that current val­
ues o f each are highly related to their own past
value one quarter earlier and three quarters
earlier, respectively, but not to earlier changes.

1The statistical analysis presented here uses variables mea­
sured in nominal terms because the credit crunch
hypothesis concerns the effects of nominal bank credit and
the latter finances, in part, nominal inventory. When the
procedures are performed on the same variables measured
in constant-dollar terms, the results are essentially the same
and the conclusions are not altered.



SEPTEMBER/OCTOBER 1992

36

To conduct the causality tests, up to eight past
values o f each variable were added to the
autoregressive model o f the other to see if
one variable is statistically significant in explaining
future values o f the other.
For loan growth during the period from II/1959
to 11/1992, the only statistically significant relation­
ship between the two measures is:
(1) L, = 2.124 + 0.236 i(1 + 0.565 Lt_,
(2.77)
(2.47)
(7.13)
R2 = 0.46
S.E. = 5.586
D.W. = 1.85
This equation indicates that inventory growth
causes business loan growth, because the
coefficient on the change in inventory (0.236) is
significantly different from zero at a 5 percent
level according to the relatively high value of
the t-statistic given in parentheses. The adjusted
R2 and Durbin-Watson (D.W.) statistics suggest,
respectively, that there is a strong relationship
and that the first lag value o f the dependent
variable (Lt l) is sufficient for removing any
problematical serial correlation in the errors o f
the estimated equation.2 No other lagged value
of i or L or combination o f lagged values is
statistically significant.
While the evidence presented here indicates
that changes in inventories result in changes in
business loans, there is nonetheless some
evidence o f reverse causality—although the
effect is ephemeral in nature. In particular, the
best time series representation for inventory
growth is an AR(3) model. The inventory
equation similar to equation 1, for the period
1/1960 to 11/1992, is:
2Both business loans and inventory are integrated of order
one and are cointegrated according to tests that are not
reported here.
Equations 1 and 2, or 1 and 3, were also estimated using
the seemingly-unrelated-regression method to allow for
contemporaneous correlations of the error terms. This does
not affect the causality conclusions. The inclusion of the lagged
residual from an estimated cointegrating vector for the levels
also does not alter these results.


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Federal Reserve Bank of St. Louis

(2) it = 1.157 + 0.560 It_, - 0.079 i(_2 + 0.274 i,_3
(1.88)
(6.32)
(-0 .8 0 )
(3.31)
+ 0.264 Lt_, - 0.216 Lt_2
(3.76)
(-3 .0 2 )
R2 = 0.55

S.E. = 4.200

D.W. = 1.92

Since the lagged terms on the change in business
loans are approximately equal in magnitude and
opposite in sign, it is possible that only a transi­
tory effect is present, so that a rise in loan
growth has no effect on inventory growth after
two quarters.
To test this hypothesis, the coefficients on the
two lags o f business loan growth were constrained
to sum to zero. The resulting estimate is:
(3) i, = 1.318 + 0.580 it_t (2.33)
(6.98)

0.067 It_2
(-0 .6 9 )

+ 0.281 It_3 + 0.241 ALt_,
(3.42)
(3.96)
R2 = 0.55

S.E. = 4.189

D.W. = 1.94

A test o f the restriction (that is, regressions 3
and 2, respectively) yields an F, 124 = 0.42, which
is not statistically significant. Thus, one cannot
reject the hypothesis that there is a transitory
causal link from increased loan growth to
increased inventory growth. After two quarters,
however, a change in business loan growth has
no statistically significant effect on business
inventory growth.3 These results suggest that
policies designed to increase bank lending, taken
alone, are unlikely to raise inventory investment,
which is one o f the principal effects expected by
proponents o f the credit crunch/recession
linkage. Moreover, these results also reaffirm the
behavior o f business loans during and
immediately following a recession.4
“According to Gilbert and Ott (1985), business loans at large
banks typically remain at their trough level during the first
year of the recovery, before giving way to moderate growth
in the second year.

37

John W. Keating
John W. Keating, assistant professor, Department o f Economics,
Washington University in St. Louis, was a visiting scholar at
the Federal Reserve Bank of St. Louis while this paper was
written. Richard I. Jako provided research assistance.

Structural Approaches to
Vector Autoregressions
1 ' HE VECTOR AUTOREGRESSION (VAR)
model o f Sims (1980) has becom e a popular tool
in empirical m acroeconom ics and finance. The
VAR is a reduced-form time series model o f the
econom y that is estimated by ordinary least
squares.1 Initial interest in VARs arose because
o f the inability o f economists to agree on the
econom y’s true structure. VAR users thought
that important dynamic characteristics o f the
econom y could be revealed by these models
without imposing structural restrictions from a
particular econom ic theory.
Impulse response functions and variance
decompositions, the hallmark o f VAR analysis,
illustrate the dynamic characteristics o f empirical
models. These dynamic indicators w ere initially
obtained by a mechanical technique that some
believed was unrelated to econom ic theory.2
Cooley and LeRoy (1985), however, argued that
this method, w hich is often described as atheoretical, actually implies a particular econom ic
structure that is difficult to reconcile with eco­
nomic theory.
This criticism led to the development o f a
"structural” VAR approach by Bernanke (1986),
Blanchard and Watson (1986) and Sims (1986).
This technique allows the researcher to use eco­
nomic theory to transform the reduced-form
1A VAR can be derived for a subset of the variables from a
linear structural model. Furthermore, it is a linear approxi­
mation to any nonlinear structural model. The accuracy of
the VAR approximation will depend on the features of the
nonlinear structure.



VAR model into a system o f structural equations.
The parameters are estimated by imposing con­
temporaneous structural restrictions. The crucial
difference between atheoretical and structural
VARs is that the latter yield impulse responses
and variance decompositions that can be given
structural interpretations.
An alternative structural VAR method, developed
by Shapiro and Watson (1988) and Blanchard and
Quah (1989), utilizes long-run restrictions to
identify the econom ic structure from the reduced
form. Such models have long-run characteristics
that are consistent with the theoretical restric­
tions used to identify parameters. M oreover,
they often exhibit sensible short-run properties
as well.
For these reasons, many economists believe that
structural VARs may unlock econom ic information
embedded in the reduced-form time series model.
This paper serves as an introduction to this
developing literature. The VAR model is shown
to be a reduced-form for a linear simultaneous
equations model. The contemporaneous and
long-run approaches to identifying structural
parameters are developed. Finally, estimates
o f contemporaneous and long-run structural
VAR models using a com m on set o f macroeconom ic variables are presented. These models
2A Choleski decomposition of the covariance matrix for the
VAR residuals.

SEPTEMBER/OCTOBER 1992

38

are intended to provide a comparison between
contem poraneous and long-run structural VAR
modeling strategies. The implications o f the
empirical results are also discussed.

and attractive assumptions are that shocks have
either temporary or permanent effects. If shocks
have tem porary effects, zt equals et, a serially
uncorrelated vector (vector white noise).5 That is,

THE V A R REPRESENTATION OF
A SIMULTANEOUS SYSTEM OF
EQUATIONS

(3) z, =

The standard, linear, simultaneous equations
model is a useful starting point for understanding
the structural VAR approach. A simultaneous
equations system models the dynamic relation­
ship between endogenous and exogenous vari­
ables. A vector representation o f this system is
(1) Axt = C(L)xt_1 + Dzt,
w here xt is a vector o f endogenous variables
and zt is a vector o f exogenous variables. The
elements o f the square matrix, A, are the struc­
tural parameters on the contem poraneous en­
dogenous variables and C(L) is a kth degree
matrix polynomial in the lag operator L, that is,
C(L) = C0+ CjL + C2L2+... + CkLT, w here all o f the C
matrices are square. The matrix D measures the
contem poraneous response o f endogenous varia­
bles to the exogenous variables.3 In theory,
some exogenous variables are observable while
others are not. Observable exogenous variables
typically do not appear in VARs because Sims
(1980) argued forcefully against exogeneity.
Hence, the vector z is assumed to consist o f un­
observable variables, which are interpreted as
disturbances to the structural equations, and x,
and zt are vectors with length equal to the num­
ber o f structural equations in the model.4
A reduced-form for this system is

(2) xt = A ‘c(L) x,_j + A 'D z (.

Alternatively, z can be m odeled as a unit root
process, that is,
(4) z, - zt_, =
Equation 4 implies that z equals the sum o f all
past and present realizations o f e. Hence, shocks
to z are permanent. The assumptions in equations
3 and 4 are not as restrictive as they might ap­
pear. If these shock processes w ere specified as
general autoregressions, the VARs would have
additional lags. The procedures to identify struc­
tural parameters, however, would be unaffected.
Under the assumption that exogenous shocks
have only temporary effects, equation 2 can be
rewritten as,
(5) xt = |5(L)xt_1 + et,
where /?(L) = A^CIL) and et = A 'De,. The
equation system in 5 is a VAR representation o f
the structural model because the last term in
this expression is serially uncorrelated and each
variable is a function o f lagged values o f all the
variables.6 The VAR coefficient matrix, f}(L), is a
nonlinear function o f the contem poraneous and
the dynamic structural parameters.
If the shocks have permanent effects, the VAR
model is obtained by applying the first difference
operator (A = 1 —L) to equation 2 and inserting
equation 4 into the resulting expression, to obtain
(6) Axt = /?(L)Axt j + et,
with /3(L) and et previously defined.

A particular structural specification for the "er­
ror term ” z is required to obtain a VAR
representation. T w o alternative, com monly used

This is a com m on VAR specification because many
m acroeconom ic time series appear to have a
unit root.7 Because o f the low pow er o f tests

3This model can accommodate lags of z; this feature is omitted,
however, to simplify the discussion.

H'his model can also be written in levels form:

4lf observable exogenous variables exist, they are included
as explanatory variables in the VAR.
sThe individual elements in a vector white noise process, in
theory, may be contemporaneously correlated. In structural
VAR practice, they are typically assumed to be independent.
6The last term represents linear combinations of serially
uncorrelated shocks, and these are serially uncorrelated as
well. See any textbook covering the basics of time series
analysis for a proof of this result.

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x, = [ A - ’ C(L) + I]xt _, - A - 1C (L)x,_2 + A - 1Dct.
Sims, Stock and Watson (1990) show that this reduced form
is consistently estimated by OLS, but hypothesis tests may
have non-standard distributions because the series have
unit roots.

39

for unit roots, their existence is controversial.
VARs can accommodate either side o f the de­
bate, how ever.8

a contemporaneous structural VAR, however,
generally does not impose restrictions on the
reduced form.

The VAR is a general dynamic specification
because each variable is a function o f lagged
values o f all the variables. This generality, h ow ­
ever, com es at a cost. Because each equation
has many lags o f each variable, the set o f varia­
bles must not be too large. Otherwise, the m od­
el would exhaust the available data.9 If all
shocks have unit roots, equation 6 is estimated.
If all shocks are stationary, equation 5 is used.10
If some shocks have temporary effects while
others have permanent effects, the empirical
model must account for this.

An alternative approach o f Doan, Litterman
and Sims (1984) estimates the VAR in levels with
a Bayesian prior placed on the hypothesis that
each time series has a unit root. The Bayesian
VAR model permits m ore lags by imposing
restrictions on the VAR coefficients, reducing
the number o f estimated parameters (called
hyper-parameters). The reduction in parameters
contributes to the Bayesian m odel’s propensity
to yield superior out-of-sample forecasts compared
with unrestricted VARs with symmetric lag
structure.

Recently, Blanchard and Quah (1989) have es­
timated a VAR model w here some variables
w ere assumed to be stationary while others had
unit roots. Alternatively, King, Plosser, Stock
and Watson (1991) use a cointegrated model,
where all the variables are difference stationary
but some linear combinations o f the variables
are stationary. The stationary linear combinations
are constructed by cointegration regressions prior
to VAR estimation. They impose the cointegration
constraints using the vector error-correction
model o f Engle and Granger (1987). Sometimes
unit-root tests com bined with theory suggest the
coefficients for stationary linear combinations.
Shapiro and Watson (1988), for example, present
evidence that the nominal interest rate and in­
flation each have a unit root while the differ­
ence between these tw o variables is stationary.
They impose the cointegration constraint by
selecting this noisy proxy for the real rate of
interest as a variable for the model.

CO N TEM PORAN EO U S STRU C­
T U R A L V A R MODELS
It is clear from equations 5 and 6 that, if the
contemporaneous parameters in A and D w ere
known, the dynamic structure represented by
the parameters in C(L) could be calculated from
the estimated VAR coefficients, that is, C(L) =
A/3(L). Furthermore, the structural shocks, t x,
could be derived from the estimated residuals,
that is, £t = D _1Aet. Because the coefficients in
A and D are unknown, identification o f structural
parameters is achieved by imposing theoretical
restrictions to reduce the number o f unknown
structural parameters to be less than or equal
to the number o f estimated parameters o f the
variance-covariance matrix o f the VAR residuals.
Specifically, the covariance matrix for the residuals,
Xe, from either equation 5 or equation 6 is

Unrestricted versions o f the VAR model (and
the error-correction model) are estimated by o r­
dinary least squares (OLS) because Zellner
(1962) proved that OLS estimates o f such a sys­
tem are consistent and efficient if each
equation has precisely the same set o f explanatory
variables. If the underlying structural model
provides a set o f over-identifying restrictions on
the reduced form , however, OLS is no longer
optimal.11 The simultaneous equations system in

An OLS estimate o f the VAR provides an estimate
o f Xe that can be used with equation 7 to obtain
estimates o f A, D and S£. The contemporaneous
structural approach imposes restrictions on
these three matrices. There are n2 elements in A,

8 Alternatively, the unit root could result from parameters in
the dynamic structural model.

10VAR lag length is often selected by statistical criteria such
as the modified likelihood ratio test of Sims (1980).

9 The lag structure of a VAR can be shown to represent vari­
ous sources of economic dynamics. Structural models with
rational expectations predict restrictions on the VAR model.
Dynamics in these models are often motivated by the costs
of adjustment to desired or equilibrium positions. The lag
structure of the VAR can also be motivated by dynamic
processes for structural disturbances.

11A two-step structural VAR estimator will generally not be
efficient if there are structural restrictions for C(L) since this
implies restrictions on /}(L). For example, Sargent (1979)
derives restrictions on VAR coefficients from a particular
model of the term structure of interest rates under rational
expectations. The full structural system is estimated by
maximum likelihood.




(7) I e =E[ete'| = a ' d e Ie/J d 'a ' 1 = a ’ d I d 'a '"1,
where E is the unconditional expectations operator,
and S£ is the covariance matrix for the shocks.

SEPTEMBER/OCTOBER 1992

40

n2 elements in D, and n (n + l)/2 unique elements
in Z£, but only n (n + l)/2 unique elements in Xe.
The maximum num ber o f structural parameters
is equal to the num ber o f unique elements in 2 .
Thus, a structural model will not be identified un­
less at least 2n2 restrictions are imposed on A,
D and XI .
Often these restrictions are exclusion restrictions;
o f course, that need not be the case. Typically,
Z£ is specified as a diagonal matrix because the
primitive structural disturbances are assumed to
originate from independent sources. The remaining
parameters are identified by imposing additional
restrictions on A and D. The main diagonal ele­
ments o f A are set to unity because each structural
equation is normalized on a particular endogenous
variable. The main diagonal for D has this same
specification since each equation has a structural
shock. These normalizations provide 2n restric­
tions. Identification requires at least 3 n (n -1 )/2 ad­
ditional restrictions based on econom ic theory.
Alternatively, the restrictions may be based on
the contemporaneous information assumed
available to particular econom ic agents following
Sims (1986). Keating (1990) and West (1990) ex­
tend this approach by showing how rational ex­
pectations restrictions can be imposed in the
contem poraneous structural VAR framework.
Except for Bernanke (1986) and Blanchard
(1989), existing models typically have not at­
tempted to identify the structural parameters
in D. Hence, D is usually taken to be the identity
matrix, leaving at least n ( n - l) /2 additional iden­
tifying restrictions to be imposed on A.
A two-step procedure is used to estimate
structural VAR models. First, the reduced-form
VAR, with enough lags o f each variable to
eliminate serial correlation from the residuals, is
estimated with OLS. Next, a sufficient number
o f restrictions is imposed on A, D and X£ to
identify these parameters. This paper obtains
the parameters in equation 7 with an algorithm
for solving a nonlinear system o f equations.
Blanchard and Quah (1989) use this approach to
estimate a structural VAR m odel.12 Standard
errors for the parameters, the impulse responses
and the variance decompositions are calculated
12Their model is identified by long-run restrictions.
13The actual residuals are randomly sampled, and the sampled
residuals are used as shocks to the estimated VAR. After
the artificial series are generated, they are used to perform
the same structural VAR analysis. After 200 replications of
the model, standard errors were calculated for the parameter
estimates, the impulse responses and the variance decom­
positions.

FEDERAL RESERVE BANK OF ST. LOUIS


using the Monte Carlo approach o f Runkle
(1987), w hich simulates the VAR model to
generate distributions for these results.13
The identification technique used in this paper
is adequate for a model in which the number o f
parameters is equal to the num ber o f unique
elements in Xe. Alternative methods are needed
to estimate a model with few er parameters.
Bernanke (1986) uses the method-of-moments
approach o f Hansen (1982) to estimate the
parameters in equation 7 and obtain standard
errors. Sims (1986) estimates the system o f
simultaneous equations for the residuals
in equation 5 using maximum likelihood.14
Blanchard and Watson (1986) also estimate the
system o f equations for residuals; however, they
employ a sequential instrumental variables tech­
nique in w hich estimated structural shocks are
used as instruments in all subsequent equa­
tions.15
The following four-equation contem poraneous
structural VAR model is used to illustrate a par­
ticular set o f such identifying restrictions. The
residuals from a VAR consisting o f the price lev­
el (p), output (y), the interest rate (r) and m oney
(m) are used in the model. This model is used in
the empirical w ork w hich follows. Equation 8
provides three restrictions by assuming that the
price level is predetermined, except that
producers can respond immediately to aggre­
gate supply shocks. Equation 9 is a reducedform IS equation that models output as a
function o f all the variables in the model. This
approach was taken instead o f explicitly m odel­
ing expected future inflation to calculate the
real interest rate and explicitly modeling the
term structure o f interest rates to tie the short­
term rate in the model with the long-term rate
predicted by theory. The IS disturbance is also
a factor in the output equation. The m oney sup­
ply function in equation 10 allows the Fed to
adjust short-term interest rates to changes in
the m oney stock. Tw o restrictions are obtained
from assuming that the Fed does not immediately
observe aggregate measures o f output and price.
The last equation is a short-run money demand
function specifying nominal money holdings as
,4ln contrast to the typical simultaneous equations model,
this approach has no observable exogenous variables.
15This technique requires a structural model for which there
are no estimated parameters in the first equation, the second
equation has one parameter, the third has two parameters,
etc. While the recursive model fits this description, this
technique can estimate a much broader set of models.

41

a function o f nominal GNP and the interest rate.
This specification is motivated by a bu ffer stock
theory w here short-run m oney holdings rise in
proportion to nominal income, yielding the final
restriction for a just-identified model. Each
equation includes a structural disturbance.
(8)

eP = £js

(9)

e[ = A,eP + A2e; + A3etm+ eJs

(10) etr = A4e^ + £tms

dynamic response o f the variables to the shocks.
If the variables in x are stationary, then the im­
pulse responses must approach zero as i b e­
comes large.
Variance decompositions allocate each variable’s
forecast error variance to the individual shocks.
These statistics measure the quantitative effect
that the shocks have on the variables. If Et (xt is
the expected value o f xt based on all information
available at time t - j , the forecast error is:
i-i

x. - e m x. = X > , £.-i'
i«0

(11) etm= As(e[ + e(p) + AGe[ + £” d
Standard VAR tools are em ployed after the
structural parameters are estimated. Impulse re­
sponse functions and variance decomposition
functions conveniently summarize the dynamic
response o f the variables to the shocks, which
is known as the moving average representation
(MAR). The MAR for the VAR is obtained by
applying simple algebra to a function o f the lag
operator. Take the VAR model for x:
xt = /3(L)xt_1 + et,
and subtract /J(L)xt t from both sides o f this
equation:

since the information at time t - j includes all £
occurring at or before time t - j and the condition­
al expectation o f future e is zero because the
shocks are serially uncorrelated. The forecast
error variances for the individual series are the
diagonal elements in the following matrix:
i-i

E(xt -

Em x ,) ( x , -

i-0
If 9ivs is the (v,s) element in 9( and as is the
standard deviation for disturbance s (s = l,...,n),
the j-steps-ahead forecast variance o f the v-th
variable is easy to calculate:
E <x v, -

E,-jx v / =

xt - /}(L)xt_, = et.
Then factor terms in xt using the lag operator,
[I - p(L) L]x( = et.
Multiply both sides o f this equation by the in­
verse o f [l-/J(L)L]:

Et_.xt) = ^ 9 ,^ 9 '.

Yj
i-0

I X

s-1

°s

v = !< 2 ,...,

n

The variance decomposition function (VDF)
writes the j-steps-ahead percentage o f forecast
error variance for variable v atributable to the
k-th shock:

E
(13) VDF(v,k,j) =

x, =[I - /}(L) L] *et.

------------- x 100.

E E c °:
i=o s-1

Insert the expression from equation 5 for et into
this last equation:
(12) xt = [I - /?(L)L J ' a 'Dc, = e(L)£t,
CO
w here 9(L) =
i =0

and each 9 i is an n x n matrix o f parameters
from the structural model. Equation 12 implies
that the response o f xt+i to £t is 9 r Hence, the
sequence o f 9 i from i = 0 ,1 ,2 ,..., illustrates the

The same analysis can be used to derive the
MAR for the VAR model in equation 6.
(14) Axt = 9(L) et,
where 9(L) = [I—/3(L) L] *A ' d . The response of
x, rather than the change in x, is frequently of
greater interest to economists. These impulse
responses can be generated recursively by as­
suming that all the elements o f £ at time zero
and earlier are equal to zero.16 For example,

16lf the pre-sample e is nonzero, its effects are lumped to­
gether with x0 which represents the initial conditions.



SEPTEMBER/OCTOBER 1992

42

LONG-RUN STR U CTU RAL V A R
MODELS

x , = xo + V ,
and
X2 = X! + 90£2 + 0 1£1'

Inserting the expression for x, into the x2 equa­
tion yields:
x 2 = x o + % £2 + <0 o + 0 , ) £r

Repeating this operation for all x up to xt, yields
the following:
t-1

x, = xo + V , + < 9o + e .K - . + -

+ <E e>)£ij-o

This result is equivalently written as
t-i
(15) x, = x0 +r(L)£t = x0 + E
i-0
i

where H =

0..
j-0

The response o f xt+ito £t is F. Since the differenced
specification assumes that Ax is stationary, the 0!
matrix goes to zero as j gets large. This implies
that l~ converges to the sum o f coefficients in
0(L). Restrictions on this sum o f coefficients are
used to identify long-run structural VAR models.
The variance decompositions for this model are
identical to equation 13 except that 0 is replaced
by r.

Shapiro and Watson (1988) and Blanchard and
Quah (1989) developed the alternative approach
o f imposing identifying restrictions on long-run
multipliers for structural shocks. An advantage
is that these models do not impose contem ­
poraneous restrictions, but they allow the data
to determine short-run dynamics based condi­
tionally on a particular long-run m odel.18
If each shock has a permanent effect on at
least one o f the variables and if cointegration
does not exist fo r the variables in x, the VAR
in equation 6 can be estimated.19 The impulse
response function fo r x in equation 15 shows
that the long-run effect o f t converges to the
sum o f coefficients in 0(L). It is obvious from
the definition o f 0(L) that replacing L by one
yields the sum o f coefficients. Hence, this sum
is conveniently written as 0(1), and this matrix
is used to parameterize long-run restrictions.
The relationship between parameters o f the
structural MAR, contem poraneous structural
parameters and VAR lag coefficients is given by
(16) 0(L) = [I-/?(L)L]~IA "1D.
The long-run multipliers are obtained by replacing
L in equation 16 with unity.
Setting L equal to unity, solving equation 16
for A ’ d and inserting the result into equation
7 yields
(17) [ l - / 3 ( l ) ] ’ 1Ee [I -P d )]" 1' = 6(1 )E £0 (1 )',

In contrast to the atheoretical VAR models
developed by Sims (1980), the structural approach
yields impulse responses and variance decom ­
positions that are derived using parameters
from an explicit econom ic m odel.17 Finding
dynamic patterns consistent with the structural
model used for identification would provide
evidence in support o f the theoretical model.
Otherwise, the theory is invalid or the empirical
model is som ehow misspecified.
,7The relationship between structural and atheoretical VARs
is addressed in the shaded insert at right.
18For example, agents may temporarily be away from longrun equilibrium positions or monetary policy may be non­
neutral in the short run.
19Unit-root tests and cointegration tests support this assump­
tion for the time series used in this paper. See Keating
(1992) for this evidence.

FEDERAL RESERVE BANK OF ST. LOUIS


where the matrix /J(l) is the sum o f VAR coeffi­
cients.
This equation can be used to identify the
parameters in 0(1) and E£. A minimal set o f
restrictions on the long-run response o f macroeconom ic variables to structural disturbances is
used to identify long-run structural VAR models.
Estimates o f the matrices on the left side of

43

The Relationship between Atheoretical and
Structural VAR Approaches
Atheoretical VAR practitioners separate the
residuals into orthogonal shocks by calculating
a Choleski decom position o f the covariance
matrix for the residuals. This decomposition
is obtained by finding the unique lower
triangular matrix A that solves the following
equation:
S e = AA'.
This statistical decomposition depends on the
sequence in which variables are ordered in x.
The residuals’ covariance matrix from a VAR
ordered by output, the interest rate, money
and the price level yields a Choleski decom ­
position that is algebraically equivalent to
estimating the following four equations by
ordinary least squares:
e-v = v?

e,r = R t f

+ K
en; = R2e> + R3 e; + v™
ep = R4e[ + Rsetr + R6e™+ vp

Hence, each v shock is uncorrelated with
the other shocks by construction. This system
implies that the first variable responds to its
ow n exogenous shock, the second variable
responds to the first variable plus an exogenous
shock to the second variable, and so on. In
practice, atheoretical VAR studies report results
from various orderings. The total num ber of
possible orderings o f the system is n!, a number

that increases rapidly with n .1 Investigators
sometimes note that certain properties o f the
model are insensitive to alternative orderings.
Results sensitive to VAR orderings are difficult
to interpret, especially if a recursive econom ic
structure is implausible.
This atheoretical approach has been criticized
by Cooley and LeRoy (1985). First, if the Choleski
technique is in fact atheoretical, then the
estimated shocks are not structural and will
generally be linear combinations o f the structural
disturbances.2 In this case, standard VAR
analysis is difficult to interpret because the
impulse responses and variance decompositions
for the Choleski shocks will be complicated
functions o f the dynamic effects o f all the
structural disturbances. The second point
attacks the claim that Choleski decompositions
are atheoretical. The Choleski ordering can
be interpreted as a recursive contemporaneous
structural model. Unfortunately, most econom ic
theories do not imply recursive contemporaneous
systems. Such criticisms o f the atheoretical
approach inspired structural approaches to
VAR modeling. If therory predicts a con­
temporaneous recursive econom ic structure,
a particular Choleski factorization o f the
covariance matrix for the residuals is appro­
priate. But a researcher using the structural
approach would not experiement with
various orderings, unless these specifications
w ere predicted by alternative theories.

’ For example, 3! = 6 but 6! = 720.
2This result is easy to prove. The Choleski decomposition
yields a system in which e. = Rv. but the true structural
model is e, = A “ 1Dct, implying tnat the shocks from the
Choleski decomposition are linear combinations of the
structural distrubances; v, = R -1 A “ 1D tt.




SEPTEMBER/OCTOBER 1992

44

equation 17 are obtained directly from the
unconstrained VAR.20 8(1) has n2 elements and
Ee has n(n + l)/2 unique elements. The n(n + l)/2
unique elements in the symmetric matrix on the
left side o f equation 17 is the number o f param­
eters in a just-identified model.21 Thus, at least
n identifying restrictions must be applied to
8(1) and Z E. The elements o f the main diagonal
for 8(1) can each be set equal to one, analogously
to the normalization used in the contem po­
raneous model. If each element o f z is assumed
to be independent, then £ . is diagonal. Hence,
n ( n - l ) /2 additional restrictions are needed for
8(1) to identify the model.
Several alternative approaches for obtaining
the structural parameters have been developed.
Shapiro and Watson (1988) impose the long-run
zero restrictions on 8(1) by estimating the
simultaneous equations model with particular
explanatory variables differenced one additional
time. King, Plosser, Stock and Watson (1991)
impose long-run restrictions using the vector
error-correction model with some o f the longrun features o f the model chosen by cointegration
regressions. Gali (1992) combines contemporaneous
restrictions with long-run restrictions to identify
a structural model. In the empirical section, we
use the approach developed by Blanchard and
Quah (1989).
Equations 18 through 21 present the long-run
identifying restrictions used in the empirical
example.22 The time subscripts are omitted
because the restrictions pertain to long-run
behavior. Three restrictions com e from equation
18, which specifies that aggregate supply shocks
are the sole source o f permanent movements in
output.23 Tw o m ore restrictions are obtained
from the long-run IS or spending balance
equation, 19, w hich specifies the interest rate as
a function o f output and the IS shock.24 Note
the coefficient Sj should be negative. The final
restriction com es from the money demand
20The Bayesian approach is not employed since a unit root is
required to be certain that shocks have permanent effects.
21An over-identified long-run model will imply restrictions on
the reduced-form coefficients.
22This is a simplified version of the model in Keating (1992).
23lf interest rates affect capital accumulation, then IS shocks
may permanently affect output and the restrictions in equation
19 may not be appropriate. If this is the only misspecification
of the model, actual money supply and money demand
shocks will be identified but the empirical aggregate supply
and IS shocks will be mixtures of these real structural
disturbances.


FEDERAL RESERVE BANK OF ST. LOUIS


function, 20, w hich sets real m oney equal to an
increasing function o f output, a decreasing
function o f the interest rate, and a money
demand shock. Equation 21 allows the supply o f
m oney to respond to all variables in the model
and a m oney supply shock.25
(18) y = £as
(19) r = S,y + £,s
(20) m - p = S2y + S3r + £md
(21) m = S ^ + S5r + S6(m -p ) + £ms

EM PIRICAL EXAM PLES AND
RESULTS
The examples from the previous tw o sections
are estimated to illustrate the long-run and
contemporaneous identification methods. Both
models use real GNP to measure output, the
GNP deflator for the price level, M l as a
measure o f the stock o f money, and the three
month Treasury bill rate determined in the
secondary market as the interest rate. The data
are first-differenced. Statistical tests suggest that
this transformation makes the data stationary.26
The first step is to estimate the reduced-form
VAR model. The estimated variance-covariance
matrix from the reduced form is used to obtain
the second-stage structural estimates. Four lags
are used for the VAR model and the sampleperiod is from the first quarter o f 1959 to the
third quarter o f 1991.

A Long-Run Structural Model
Table 1 reports the parameter estimates for
the long-run model in equations 18 through 21.
The first four parameters are standard deviations
for the structural shocks, and each o f these
24Technically, the IS equation should use the real interest
rate, an unobservable variable. However, if permanent
movements in the nominal rate and the real rate are identical,
this specification is legitimate. This would be true, for
example, if the Fisher equation held and if inflation followed
a stationary time series process.
25Thus, 9(1) is:

1 0

-S .

1

0 0
0

0

-S 2 -S 3 1 0
-S 4 -S 5 -S 6 1
26For empirical evidence, see the unit-root tests in Keating
(1992).

45

Table 1
Estimates for the Long-Run Model
°as
°is
°md
°ms
si
S2
S3
s4

S5
s6

Parameter

Standard error

.0144*
.0092*
.0149*
.0172*
-.117 1
.8722*
-2 .2 7 6 *
-1 .4 1 1 *
1.569
.9048*

.0041
.0028
.0031
.0042
.3068
.4219
.7083
.5778
1.020
.3842

NOTE: An asterisk (*) indicates significance at the 5
percent level.

estimates is significantly different from zero.
The coefficient in the IS equation, S,, is negative
as hypothesized, but insignificantly different from
zero. Each parameter in the m oney demand
function is statistically significant and has the
sign predicted by econom ic theory. The coefficient
on real GNP, S2, is not statistically different from
one. Parameters for the m oney supply equation
can be interpreted as a policy reaction function
in which the Fed reduces m oney if output rises
but increases m oney if interest rates rise. This
last effect is not statistically significant. The
increase in money in response to an increase in real
money may reflect the fact that the Fed has typically
smoothed interest rate fluctuations in the post­
war period, so that a money demand shock that
raises real money will be accommodated by a
comparable increase in nominal money.
The impulse responses fo r the long-run model
are shown in figures 1 through 4. Point estimates
and 90 percent confidence intervals are graphed
for the variables. If the long-run parameter
estimates are consistent with the theoretical
model, the asymptotic properties o f the impulse
responses must also be consistent with the
theory. Economic restrictions are not imposed
on the dynamic properties o f the model. The
empirical aggregate supply shock raises output
and real m oney and lowers the interest rate,
the price level and nominal money. The real
spending shock raises output only temporarily
because o f the restriction that aggregate supply
shocks are the only factor in long-run output
movements. The interest rate and the price
level rise, while the nominal and real measures
o f money decline after each variable initially
rises by a small amount. The m oney demand



shock has a strong positive effect on nominal
and real money. The other effects are relatively
weak, with prices falling, output temporarily
falling and the interest rate temporarily rising.
Money and the price level both rise in response
to an increase in the m oney supply, w hich also
causes a temporary decline in the interest rate
and a temporary increase in output and real
money. The impulse response functions provide
evidence that the shocks affect each variable as
theory predicts.
The variance decompositions in table 2 show
the average amount o f the variance o f each
variable attributable to each shock. Standard
errors for these estimates are in parentheses.
The output variance due to the supply shock
one quarter in the future is only 17 percent.
Eight quarters in the future, however, the
estimate becom es nearly half o f output’s
variance and, at 48 quarters, 90 percent o f the
variance o f output is attributed to supply shocks.
Variability in the price level is dominated by
aggregate supply shocks, particularly in the
short run. The other shocks have temporary
output effects. This long-run feature is obtained
because the model forces aggregate supply shocks
to explain all permanent output movements. Shortrun output movements are dominated by real
spending shocks. This shock explains most of
the interest rate variance and the variance of
real m oney in the long run. The money supply
shock has a gradual effect on output that peaks
at 13 percent o f the variance tw o years in the
future. This shock accounts for a large portion
o f the short-run variance o f the interest rate
and the long-run movement in nominal money.
The money demand shock has virtually no effect
on output, in terest rates o r prices. M an y th eories

predict that m oney demand shocks will not
have much effect on these variables if the Fed
uses the interest rate as its operating target.
Money demand shocks have strong effects on
nominal m oney and real money. In general, the
results for this model are consistent with most
economists’ views about econom ic behavior,
although some might be surprised by the
relatively small effect on output o f money
supply disturbances.

Contemporaneous Structural Model
The parameter estimates for the contem porane­
ous model in equations 8 through 11 are reported
in table 3. The coefficients in the reducedform IS equation are all negative. The negative

SEPTEMBER/OCTOBER 1992

46

Figure 1
Responses to an Aggregate Supply Shock in
the Long-Run Model
Output

Price

Interest Rate

0.03

Real Money


http://fraser.stlouisfed.org/
FEDERAL RESERVE BANK OF ST. LOUIS
Federal Reserve Bank of St. Louis

NOTE: The dashed lines enclose 90 percent
confidence intervals which were calculated
using Runkle's (1987) Monte Carlo simulation
method.

47

Figure 2
Responses to a Real Spending Shock in the
Long-Run Model




Output

Price

Interest Rate

Real Money
NOTE: The dashed lines enclose 90 percent
confidence intervals which were calculated
using Runkle's (1987) Monte Carlo
simulation method.

SEPTEMBER/OCTOBER 1992

48

Figure 3
Responses to a Money Demand Shock in the
Long-Run Model
Price

0.006
0.004
0.002
0
-

0.002

-0.004
-0.006
-0.008
-

0.01

1

7

13

Interest Rate

19 25

31

37

43 49

37

43 49

Money
0.0225
0.02

0.0175
0.015
0.0125
0.01

0.0075
0.005
0.0025
0

1

7

13

19 25

31

Real Money


http://fraser.stlouisfed.org/
FEDERAL RESERVE BANK OF ST. LOUIS
Federal Reserve Bank of St. Louis

NOTE: The dashed lines enclose 90 percent
confidence intervals which were calculated
using Runkle's (1987) Monte Carlo simulation
method.

49

Figure 4
Responses to a Money Supply Shock in the
Long-Run Model
Output

Interest Rate

Price

Money

0.0016




Real Money
NOTE: The dashed lines enclose 90 percent
confidence intervals which were calculated
using Runkle's (1987) Monte Carlo
simulation method.

SEPTEMBER/OCTOBER 1992

50

Table 2
Variance Decompositions for the Long-Run Model

Variable

Quarter(s)
ahead

Aggregate
supply
shock

Real
spending
shock

Money
demand
shock

Money
supply
shock

1
2
4
8
16
32
48

17(24)
16 (23)
24 (25)
45 (23)
67 (15)
84 ( 8)
90 ( 5)

76
78
65
42
24
11
7

(24)
(24)
(24)
(19)
(13)
( 7)
( 5)

1(
1(
0(
0(
0(
0(
0(

8)
8)
6)
4)
2)
1)
1)

7(16)
5(14)
11 (14)
13(11)
9 ( 7)
5 ( 3)
3 ( 2)

1
2
4
8
16
32
48

13 (13)
14(13)
13(11)
8(10)
5(11)
4(13)
4(14)

49
57
71
84
91
94
95

(25)
(23)
(15)
(12)
(12)
(13)
(14)

1(
1(
3(
2(
1(
1(
0(

8)
7)
5)
3)
2)
1)
1)

37 (23)
27 (19)
13 ( 9)
6 ( 6)
3 ( 4)
1 ( 2)
1 ( 1)

1
2
4
8
16
32
48

7(11)
12 (14)
18 (17)
26 (19)
25 (19)
26 (21)
27 (22)

2(10)
3 ( 8)
8(12)
24 (17)
38 (20)
44 (21)
45 (21)

90
73
59
41
33
29
28

(17)
(18)
(19)
(18)
(18)
(19)
(19)

2(11)
12(14)
14 (14)
9(10)
4 ( 5)
2 ( 3)
1 ( 1)

1
2
4
8
16
32
48

6(10)
3 ( 9)
1 ( 9)
0(10)
1 (11)
4(13)
6(15)

5(14)
2(10)
3(11)
10 (15)
14(17)
11 (17)
9(17)

73
63
59
50
46
41
39

(22)
(22)
(23)
(21)
(20)
(19)
(19)

15
32
38
40
39
44
46

(20)
(21)
(22)
(21)
(20)
(20)
(20)

9(13)
5(10)
2 ( 8)
1 ( 7)
0 ( 7)
0 ( 7)
0 ( 7)

16
12
13
16
20
23
24

(23)
(21)
(21)
(20)
(19)
(19)
(19)

Output

Interest Rate

Real Money

Money

Price
1
2
4
8
16
32
48

73
78
77
69
60
55
54

(27)
(27)
(28)
(28)
(27)
(27)
(27)

NOTE: Standard errors are in parentheses.


FEDERAL RESERVE BANK OF ST. LOUIS


2(12)
4(14)
7(16)
15 (19)
20 (21)
22 (21)
22 (22)

51

Table 3
Estimates for the Contemporaneous
Model
°as
°is
°ms
°md
Ai
a2
A3
A4
A5
A6

Parameter
.0038*
.0086*
.0087
.0087
-.1164
- .0469
- .3327
1.030
.5632
- .9397

Standard error
.0003
.0027
.0419
.0324
.3255
.4122
.6539
8.302
2.098
5.737

NOTE: An asterisk (*) indicates significance at the 5 percent
level.

coefficient on money would be unexpected in a
structural IS equation; however, these estimates
are reduced-form coefficients, not structural pa­
rameters. The coefficient on m oney in the
interest rate equation is positive. This supports
the view that the central bank attempts to
stabilize money growth by raising interest rates.
In the money demand equation, the coefficient
on nominal spending is roughly one-half, and
the interest rate coefficient is almost -1 .0 .
Hence, the parameter estimates in this structural
model are consistent with econom ic theory.
Unfortunately, each o f these structural para­
meters is statistically insignificant.
Figures 5 through 8 plot the impulse responses.
In contrast to the long-run model, the aggregate
supply equation is normalized on the price
level. Hence, an aggregate supply shock raises
the price level and reduces output. The aggre­
gate supply shock has this expected effect on
prices and output. Real money also decreases.
The adverse supply shock has a weak positive
effect on money and the interest rate. The IS
shock raises prices, output and the interest rate.
Real and nominal money initially increase,
although both subsequently fall. The money
supply equation is normalized on the interest
rate so a reduction in the supply o f m oney raise
interest rates. This shock raises the interest rate
and causes a decline in nominal money, real
money and the price level. Surprisingly, output
rises briefly before it begins to decline. The
money demand shock causes the interest rate,
nominal and real money to increase while
output falls. The rising price level is inconsistent



with theory, although this effect is not
statistically significant. In contrast with the longrun model, there are a few unusual features in
the impulse responses for the contemporaneous
specification. Most o f the dynamic patterns,
however, are consistent with the structural
model.
The variance decompositions for the con ­
temporaneous model are shown in table 4.
Many features o f this table are comparable to
the long-run model's results. For example, the
aggregate supply shock gradually explains most
o f output’s variability, is the most important
shock for the price level and is never an
important source o f interest rate movements.
The IS shock is the most important source of
short-run output movement, and it explains
most o f the long-run variance o f the interest
rate. Some results, however, are considerably
different com pared with the results from the
long-run model. The m oney demand shock has
its greatest effect on output in the long run.
This shock explains a large amount o f the shortrun variance o f the interest rate but virtually
none o f the long-run variance o f real or
nominal money balances. The money supply
shock has essentially no effect on output, while
accounting for a large amount o f the variance
in real money, even in the long run, and none
o f the variance o f prices. These results are
inconsistent with most m acroeconom ic theories.

CONCLUDING REM ARK S
This paper outlines the basic theory behind
structural VAR models and estimates tw o models
using a standard set o f m acroeconom ic data.
The results for the tw o specifications are often
similar. The long-run structural VAR model in
this paper generally provides empirical results
that are consistent with the structural model.
Some o f the variance decompositions and the
impulse responses for the contemporaneous
model w ere inconsistent with standard macroeconom ic theory. These inconsistencies pertain
to the effects o f m oney supply and money
demand disturbances. Another result is that
structural parameters in the long-run model are
more precisely estimated than parameters in the
contemporaneous model. W herever a significant
discrepancy exists between the two models, the
model with long-run restrictions yields sensible
results, while the results from the contemporaneous
model are inconsistent with standard econom ic
theories.

SEPTEMBER/OCTOBER 1992

52

Figure 5
Responses to an Aggregate Supply Shock in
the Contemporaneous Model
Price

Interest Rate


FEDERAL RESERVE BANK OF ST. LOUIS


Money

NOTE: The dashed lines enclose 90 percent
confidence intervals which were calculated
using Runkle's (1987) Monte Carlo
simulation method.

53

Figure 6
Responses to a Real Spending Shock in the
Contemporaneous Model
Output

0.015

0.0075

1

0.015J
1

>
/

0.01250.01

-

/

0.005
0.0025 A

Price

0.02

0.010.005-

\

n /

0

-0.0025 ----- 1-------1------- 1-------1------ 1-------1-------1-----1
7 13 19 25 31 37 43 49
Interest Rate

0 .006-1




-0.005-

'

I

i

13

”!

19

! .......!

25

31

!

37

r

43

49

Money

Real Money
NOTE: The dashed lines enclose 90 percent
confidence intervals which were calculated
using Runkle's (1987) Monte Carlo
simulation method.

SEPTEMBER/OCTOBER 1992

54

Figure 7
Responses to a Money Supply Shock in the
Contemporaneous Model
Price

Interest Rate


FEDERAL RESERVE BANK OF ST. LOUIS


NOTE: The dashed lines enclose 90 percent
confidence intervals which were calculated
using Runkle's (1987) Monte Carlo
simulation method.

55

Figure 8
Responses to a Money Demand Shock in the
Contemporaneous Model
Output

Price

Interest Rate
0.01

0.0075- i \ , \
0.0050.0025

V\

0

-0.0025-

\ _ _______

-0.005




NOTE: The dashed lines enclose 90 percent
confidence intervals which were calculated
using Runkle's (1987) Monte Carlo
simulation method.

SEPTEMBER/OCTOBER 1992

56

Table 4
Variance Decompositions for the Contempo raneous Model

Variable

Quarter(s)
ahead

Aggregate
supply
shock

Real
spending
shock

Money
demand
shock

Money
supply
shock

2 ( 4)
3 ( 5)
1 ( 3)
2 ( 5)
2 ( 7)
2 ( 9)
2(10)

Output
1
2
4
8
16
32
48

1 ( 2)
1 ( 3)
3 ( 5)
12 (10)
28 (16)
47 (21)
55 (23)

94
93
91
73
51
31
23

(16)
(16)
(15)
(19)
(20)
(21)
(22)

4(14)
3(13)
5(13)
13(14)
19 (14)
20 (14)
20 (14)

1
2
4
8
16
32
48

2 ( 2)
4 ( 4)
10 ( 7)
8 ( 6)
8 ( 7)
8(10)
8(11)

12 (12)
17(13)
38 (15)
56 (18)
63 (20)
67 (22)
68 (22)

37 (26)
34 (24)
27 (18)
19 (16)
12(15)
9(14)
8(14)

49
44
25
17
16
16
15

(31)
(30)
(23)
(20)
(20)
(20)
(20)

1
2
4
8
16
32
48

19
18
24
34
38
42
45

( 7)
( 8)
(11)
(13)
(16)
(20)
(21)

11 (14)
5(11)
2 ( 8)
4 ( 7)
10 (10)
14(12)
15(12)

36 (21)
16 (18)
6(16)
2(14)
1 (15)
0(15)
0(16)

34
60
68
61
51
44
40

(22)
(20)
(19)
(19)
(21)
(23)
(24)

2 ( 2)
1 ( 2)
0 ( 2)
0 ( 3)
1 ( 6)
4(10)
7(13)

14 (15)
7(12)
3(10)
1 ( 9)
1 (11)
1 (11)
0(11)

44 (24)
23 (22)
13 (21)
7(20)
6 (20)
7(20)
7(20)

41
68
83
92
92
89
86

(31)
(27)
(26)
(25)
(25)
(25)
(25)

Interest Rate

Real Money

Money
1
2
4
8
16
32
48
Price
1
2
4
8
16
32
48

100
98
95
89
84
82
81

( 0)
( 2)
( 4)
( 7)
(10)
(11)
(12)

NOTE: Standard errors are in parentheses.


FEDERAL RESERVE BANK OF ST. LOUIS


0 ( 0)

0( 1)
2
6
12
14
15

( 2)
( 6)
( 8)
( 9)
(10)

0(
2(
3(
4(
4(
3(
3(

0)
1)
3)
5)
6)
7)
7)

0(
0(
0(
0(
0(
1(
1(

0)
1)
2)
5)
7)
9)
9)

57

These comparisons betw een contem poraneous
and long-run specifications may not generalize
to all structural VAR applications, but they sug­
gest that long-run structural VARs may yield
theoretically predicted results m ore frequently
than VARs identified with short-run restrictions.
This result is not surprising. One reason is that
econom ic theories may often have similar longrun properties but different short-run features.
For example, while output movements are driven
solely by aggregate supply shocks in a typical
real business cycle model, supply shocks will ac­
count for permanent output movements in
Keynesian models, but every shock may have
some cyclical effect. In addition, long-run struc­
tural VAR models may provide superior
results because they typically do not impose
contem poraneous exclusion restrictions. Keating
(1990) shows that contem poraneous "zero”
restrictions may be inappropriate in an environ­
ment with forward-looking agents w ho have ra­
tional expectations. The intuition behind this
result is that any observable contemporaneous
variable may provide information about future
events. One implication from that paper is that
different short-run restrictions can be obtained
from alternative assumptions about available in­
formation. Further research should investigate
other examples o f contem poraneous and longrun structural VAR models to determine whether
the superior perform ance o f this paper’s long-run
model is a special case or a m ore general result.

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Sargent, Thomas J. “ A Note on Maximum Likelihood Estimation
of the Rational Expectations Model of the Term Structure,”
Journal of Monetary Economics (January 1979), pp. 133-43.
Schwert, G. William. “ Effects of Model Specification on Tests
for Unit Roots in Macroeconomic Data,” Journal of Monetary
Economics (July 1987), pp. 73-104.
Shapiro, Matthew D., and Mark W. Watson. “ Sources of
Business Cycle Fluctuations,” in Stanley Fischer, ed.,
NBER Macroeconomics Annual 1988 (MIT Press, 1988),
pp. 111-48.
Sims, Christopher A. “ Are Forecasting Models Usable for
Policy Analysis?” Federal Reserve Bank of Minneapolis
Quarterly Review (Winter 1986), pp. 2-16.
_______ “ Macroeconomics and Reality,” Econometrica
(January 1980), pp. 1-48.
Sims, Christopher A., James H. Stock, and Mark W. Watson.
“ Inference in Linear Time Series Models with Some Unit
Roots,” Econometrica (January 1990), pp. 113-44.
Stock, James H., and Mark W. Watson. “ A Simple Estimator
of Cointegrating Vectors in Higher Order Integrated Systems,”
Federal Reserve Bank of Chicago Working Paper WP-91-4,
(February 1991).
_______ “ Testing for Common Trends,” Journal of the
American Statistical Association (December 1988), pp. 1097107.
_______ “ Variable Trends in Economic Time Series,” Journal
of Economic Perspectives (Summer 1988), pp. 147-74.
West, Kenneth D. “ The Sources of Fluctuations in Aggregate
Inventories and GNP,” Quarterly Journal of Economics
(November 1990), pp. 939-71.
Zellner, Arnold. “ An Efficient Method of Estimating Seeming­
ly Unrelated Regressions and Tests for Aggregation Bias,”
Journal of the American Statistical Association (June 1962),
pp. 348-68.

SEPTEMBER/OCTOBER 1992

58

Anna J. Schwartz,
Anna J. Schwartz is a Senior Research Fellow at The National
Bureau of Economic Research. This paper was the sixth annu­
al Homer Jones Memorial Lecture, which was presented at St.
Louis University on April 9, 1992. The views expressed are
those of the author and do not reflect official positions of the
Board of Governors of the Federal Reserve System or the Fed­
eral Reserve Bank of St. Louis.
The Homer Jones Memorial Lecture is an annual event
sponsored by the St. Louis Gateway Chapter of the National
Association of Business Economists in conjunction with
Washington University, St. Louis University, the University of
Missouri-St. Louis and the Federal Reserve Bank of St. Louis.
Author’s note: For sharing his knowledge of Federal Reserve
practices, Walker F. Todd has been immensely helpful to me,
but he is not responsible for the views I express in this paper.
I have also benefited from comments by Allan H. Meltzer.

The Misuse of the Fed's
Discount Window

I
AM HONORED to have the opportunity to
give the Homer Jones Memorial Lecture. In
remembering him today, I pay tribute to his
contributions to monetary policy making and to
quantitative monetary research in his capacity
as director o f research at the St. Louis Fed. I
got to know Homer during the period o f his
membership in the Shadow Open Market Com­
mittee. At our meetings he was diffident about
his knowledge and insistent on scrupulous at­
tention to statistical evidence as backing for the
policy conclusions w e reached. I cannot think of
tw o more admirable qualities in an economist. It
was a privilege for me to have had this associa­
tion with Homer.
In 1925 the Federal Reserve Board collected
data on the number o f m em ber banks continu­
ously indebted to their Reserve Banks for at
least a year. As o f August 31, 1925, 593 m em­
ber banks had been borrow ing for a year or
more. Of this number, 239 had been borrow ing
since 1920 and 122 had begun borrow ing before
that. The Fed guessed that at least 80 percent o f

FEDERAL RESERVE BANK OF ST. LOUIS


the 259 national member banks that had failed
since 1920 had been "habitual borrow ers” prior
to their failure. Of 457 continuous borrow ers in
1926, 41 banks suspended operations in 1927,
while 24 liquidated voluntarily or merged (Shull
1971, 34-35).
The reason for citing these statistics for the
1920s is to call attention to an early episode in
Federal Reserve history that contravened the
ancient injunction to central banks to lend only
to illiquid banks, not to insolvent ones, and that
is eerily similar to a current episode. The Fed
apparently learned little from the earlier epi­
sode, since there is even less justification for
the use made o f the discount window in the
current than in the earlier episode.
The current episode came to light after the
House Banking Committee requested data on all
insured depository institutions that borrow ed
funds from the discount w indow from January
1, 1985, through May 10, 1991. Regulators
grade banks on their perform ance, according to

59

a scale o f 1 to 5. The grades are based on five
measures known by the acronym o f CAMEL,
for Capital adequacy, Asset quality, Manage­
ment, Earnings, Liquidity.1 The Federal Reserve
reported that o f 530 borrow ers from 1985 on
that failed within three years o f the onset of
their borrowings, 437 w ere classified as most
problem-ridden with a CAMEL rating o f 5, the
poorest rating; 51 borrow ers had the next
lowest rating, CAMEL 4. One b orrow er with a
CAMEL rating o f 5 remained open for as long
as 56 months. The whole class o f CAMEL
5-rated institutions w ere allowed to continue
operations for a mean period o f about one year.
At the time o f failure, 60 percent o f the b o r­
row ers had outstanding discount w indow loans.
These loans w ere granted almost daily to insti­
tutions with a high probability o f insolvency in
the near term, new borrow ings rolling over
balances due. In aggregate, the loans o f this
group at the time o f failure amounted to $8.3
billion, o f which $7.9 billion was extended when
the institutions w ere operating with a CAMEL 5
rating. Three months prior to failure, b orrow ­
ings o f all 530 institutions peaked at $18.1 bil­
lion. Rather than encouraging banks to pursue
strategies to preserve their size, regulators often
encourage institutions that are about to fail to
shrink drastically first, so as to diminish the
pool o f assets that have to be liquidated after
closing.
Some observers o f bank perform ance have as­
serted that it is impossible to know whether an
institution that applies for discount w indow as­
sistance faces a liquidity or solvency problem.
That assertion may be defensible for discount
w indow lending in the 1920s even though an
estimated 80 percent o f long-time borrow ers

1Brief official descriptions of composite CAMEL 4 and 5 rat­
ings follow:
CAMEL 4 “ Institutions in this group have an immoder­
ate volume of serious financial weaknesses or a combi­
nation of other conditions that are unsatisfactory. Major
and serious problems or unsafe and unsound conditions
may exist which are not being satisfactorily addressed or
resolved."
CAMEL 5 “ This category is reserved for institutions
with an extremely high immediate or near-term probability
of failure.”
CAMEL ratings of banks are not uniform from one district
to another. Some New York CAMEL 4 banks may be rated
5 elsewhere.

failed, since CAMEL ratings did not then exist.
Currently, CAMEL ratings 4 and 5 are known
promptly. W hy should it be impossible or even
difficult to distinguish between an illiquid and
an insolvent bank?
Support by the Fed for banks with a high
probability o f insolvency in the near term is not
the only recurrent problem with the discount
window. Equally troublesome is the history of
actual or proposed Fed capital loans to non­
banks. Such use o f the discount w indow dis­
tracts the Fed’s attention from its monetary
control function. Recent experience reinforces
earlier doubts about the need for the discount
window. The time has com e for a truly basic
change: eliminate the discount w indow and retrict the Fed to open market operations.2 This
change would have the added value o f obliterat­
ing the symbolic role o f the discount rate and
weakening the tendency to regard the Fed as
determining interest rates.
In the rest o f this paper, I document the ero­
sion o f the historic restriction, at least since the
1930s, o f Federal Reserve discount w indow assis­
tance to liquidity-strained banks on the security
o f sound assets. Section 1 deals with lending
operations from the founding until the postW orld War II period, during which loans to
nonbanks first occur. I then discuss Federal
Reserve actions in recent decades that have fu r­
ther blurred the distinction between liquidity
and solvency, and also the emergence o f various
nonbanks as candidates for discount w indow as­
sistance. I ask why these developments have o c­
curred w hen there has been no change in official
declarations o f commitment to supply only li­
quidity, not solvency or capital, to individual
banks, not nonbanks (section 2). In the next sec-

changes would eliminate the problem of political pressures
on the Fed to lend to nonbanks. As for the problem of
loans to insolvent banks, access to the window as a right
at a penalty rate might only result in worsening adverse
selection.
See also Kaufman (1991), who argues that the discount
window is not needed to protect the money supply — the
basic justification for a lender of last resort — and that li­
quidity strains can be mitigated by open market operations
without involving the Fed in discount window assistance.
Credit-worthy banks can borrow at market rates, large ones
in the Fed Funds market, small ones from their correspon­
dent banks.

2This recommendation has been disputed on the ground
that establishing access to the discount window as a right
— not a privilege — administered at a penalty rate would
solve the problems that face the current administration of
the window. It is not clear to me, however, that these



SEPTEMBER/OCTOBER 1992

60

tion I examine the costs o f Federal Reserve sup­
port for problem institutions that regulatory
authorities eventually close and for nonbanks
that would otherwise have to meet a market
test (section 3). Finally, I consider whether re­
form s o f discount w indow practices that have
been proposed could rem edy the inherent
problems o f the mechanism. I comment on p ro­
visions in the FDIC Improvement Act o f 1991
that may be w orthy reform proposals but do
not address these problem s (section 4). I offer
my conclusions in section 5.

appears in an internal Federal Reserve history
o f the discount mechanism: "extended b o rro w ­
ings by a m em ber bank from its Reserve Bank
would in effect constitute a use o f Federal
Reserve credit as a substitute for the m em ber’s
capital” (Hackley 1973, 194). The 1973 version
o f Regulation A states, as a general principle,
that "Federal Reserve credit is not a substitute
for capital and ordinarily is not available for ex­
tended periods.” Both the 1980 and 1990 ver­
sions o f Regulation A state, as a general require­
ment, that "Federal Reserve credit is not a sub­
stitute for capital.”

1. H ISTORIC ROLE OF DISCOUNT
W IN D O W LENDING

A broader statement o f the foregoing princi­
ple, covering banks and nonbanks, appeared in
1932 in a conference report by representatives
o f the Federal Reserve Bank o f New York, w ho
had met with South American central banks:
"Central banks must not in any way supply cap­
ital on a permanent basis either to m ember
banks or to the public, which may lack it for
the conduct o f their business” (Federal Reserve
Bulletin 1932, 43).

A. B efore the New Deal
Regulation A—the first one adopted by the
Federal Reserve Board at its creation, in recogni­
tion o f the expectation that the discount w indow
at Federal Reserve Banks would serve as the
main purveyor o f m em ber bank reserves—
establishes the rules under w hich the Banks
may extend credit. Periodically revised, the regu­
lation has consistently set out the procedures
that banks had to follow to gain access to the
discount w indow . The initial regulation provid­
ed for rediscounting short-term agricultural, in­
dustrial, and commercial paper, defined as
eligible paper. Later, to accommodate Treasury
financing needs in W orld W ar I, the Reserve
Banks w ere em pow ered to extend direct col­
lateral loans to m em ber banks, occasionally se­
cured by pledge o f eligible paper but usually by
obligations o f the U.S. government. Until the
1930s, even though the Federal Reserve had be­
com e familiar with open market purchases as a
source o f member bank reserves, bills discount­
ed usually exceeded U.S. government securities
in Reserve Bank portfolios.
The discount w indow provided accom m oda­
tion for periods up to 90 days for a nonagricultural discount or advance collateralized
by eligible paper or governm ent obligations, but
o f up to nine months for agricultural paper. As
noted earlier, continuous borrow ing year in and
year out in the 1920s was not uncom m on. A
later (1954) Federal Reserve document, deploring
continuous borrow ing, noted that "it was possi­
ble by the mid-Thirties to speak o f an estab­
lished tradition against member bank reliance
on the discount facility as a supplement to its
resources” (Shull 1971, 41). A similar statement

http://fraser.stlouisfed.org/
FEDERAL RESERVE BANK OF ST. LOUIS
Federal Reserve Bank of St. Louis

Legislative changes in the administration of
the discount window, made in response to bank
failures in the Great Depression, sometimes o b ­
served this advice. The Glass-Steagall Act o f
February 27, 1932, authorized Federal Reserve
Banks (in a new section 10(b) added to the Fed­
eral Reserve Act) to make advances to member
banks on their promissory notes secured by
otherwise ineligible collateral, if acceptable to
the Reserve Banks, for periods up to four months
at rates not less than one-half percent per an­
num above the prevailing highest discount rate.
No provision was made for solvency loans of
capital or loans to receivers o f closed banks.
Although no provision was made for solvency
loans o f capital, the Emergency Relief and Con­
struction Act o f July 21, 1932 (in a new section
13(3) added to the Federal Reserve Act), opened
the discount w indow to nonbanks. It permitted
the Reserve Banks to discount for individuals,
partnerships and corporations, with no other
sources o f funds, notes, drafts and bills o f ex­
change eligible for discount for member banks.
The New Deal confirm ed this type o f authority
(in section 403 o f Title III o f the Emergency
Banking Act o f March 9, 1933, that added section
13(13) to the Federal Reserve Act). It allowed
90-day advances to individuals, partnerships and
corporations on the security o f direct obliga­
tions o f the U.S. government, at interest rates
fixed by the Reserve Banks.

61

B. From the New Deal to PostWorld II
Before turning to the New Deal change that
involved Reserve Banks in extending capital
loans to nonbanks, let me review the other
changes in the Emergency Banking Act o f 1933.
Title II created conservatorships for national
banks. Section 304 of Title III authorized the
Reconstruction Finance Corporation, not the
Federal Reserve, to subscribe to preferred stock
"o f any national banking association or any
State bank or trust com pany in need o f funds
for capital purposes.” It is significant that Title
IV, referring to the Federal Reserve, conferred
on it no authority to make solvency loans of
capital. Section 402 authorized Federal Reserve
Banks, until March 3, 1934, to make advances in
exceptional and exigent circumstances to mem­
ber banks on their ow n notes on the security of
any acceptable assets, superseding the provision
regarding advances to m em ber banks in the
February 1932 Glass-Steagall Act. By Presidential
proclamation, this provision, the forerunner of
the present section 10(b), was extended until
March 3, 1935, w hen it expired (Board Annual
Report 1933, 261-265). The new form o f section
10(b) becam e permanent as part o f the Banking
Act o f 1935.
I now turn to the New Deal change that
authorized the Federal Reserve to make solvency/
capital loans to nonbanks. The Act o f June 19,
1934, added a new section 13(b) to the Federal
Reserve Act, which authorized Reserve Banks
directly or in participation with a member or
nonmem ber bank to make advances to estab­
lished commercial or industrial enterprises for
the purpose o f supplying working capital if the
borrow er w ere unable to obtain assistance from
usual sources. A participating m em ber or nonmember bank had to obligate itself for at least
20 percent o f any loss. The loans w ere for peri­
ods up to five years (Board A nnual Report 1934,
50-51). Through 1939, the Reserve Banks had
approved 2,800 applications and commitments
amounting to $188 million at rates from 2.5 to 6
percent (Smead 1941, 259). Although the Recon­
struction Finance Corporation then assumed a
more important role in providing working capi­
tal for established businesses, the Reserve Banks
continued to participate, approving an additional
742 applications amounting to $382 million
through 1946 (Board Annual Report 1946, 10).
The aggregate amount of such loans was limit­
ed by law to the surplus o f the Reserve Banks



as o f July 1, 1934, plus $139 million that the
Treasury was to repay the Banks for their re­
quired subscription to the Federal Deposit In­
surance Corporation in an amount equal to
one-half o f their surplus on January 1, 1933.
The required subscription was stipulated in the
Banking Act o f 1933 that created the FDIC
(Board Annual Report 1933, 276-277). A com m en­
tator has noted that this "is the only instance in
United States history in which Congress re­
quired the central bank to expend its ow n
funds to subscribe for more than a de m inim is
amount o f the capital o f another unrelated en­
terprise, other than obligations o f the Treasury
itself” (Todd 1988, 60). In any event, the
Reserve Banks charged o ff the value o f FDIC
stock on their books in the same calendar year
in which they paid fo r the subscription. Capital
loans to nonbanks under the authority o f sec­
tion 13(b), unlike the FDIC subscription, w ere
voluntary decisions o f the Reserve Banks. In
section 2 below, I note a more recent attempt
by the Treasury that was foiled to require the
Fed to expend its ow n funds in support o f the
FDIC.
Congressional authorization and Federal
Reserve implementation o f loans to nonbanks
for use as capital was, in my judgment, a sorry
reflection on both Congress's and the Fed’s un­
derstanding o f the System’s essential monetary
control function. In 1946 the Federal Reserve
Board sought to eliminate its authority under
section 13(b) to make loans directly to business
enterprises and replace it with a mandate re­
stricted to guaranteeing such loans. A bill in­
troduced in Congress early in 1947 on the
Board's behalf would have authorized Reserve
Banks to guarantee, up to a maximum o f 90
percent, loans, extended by banks for as long as
10 years to small- and medium-size business en­
terprises, subject to a fee charge that increased
with the guarantee percentage. The bill also
provided for the return o f the amounts ad­
vanced by the Treasury (up to $139 million) for
the Banks’ industrial loan operations, and
pledged that no further Treasury appropriations
for this purpose would be required (Board A n­
nual Report 1946, 8-10; 1947, 11-12).
Since the bill was not enacted, Reserve Banks
for the next decade continued to make and co ­
finance working capital industrial loans. Section
13(b) was finally repealed by the Small Business
Investment Act o f 1958, under the terms of
which the Reserve Banks restored to the Trea­
sury the amounts it had advanced under section

SEPTEMBER/OCTOBER 1992

62

13(b) (Board A nnual Report 1958, 95). Chairman
William McChesney Martin, in testimony before
the Subcommittee on Small Business o f the
Senate Banking and Currency Committee, when
it was considering this bill, stated well the Fed­
eral Reserve’s considered judgment on its ven­
ture into capital industrial loans: Its primary
objective was “guiding monetary and credit poli­
cy,” and "it is undesirable for the Federal
Reserve to provide the capital and participate in
management functions" o f the proposed small
business financing institutions (Federal Reserve
Bulletin 1957, 769).
I conclude this survey o f Federal Reserve
lending activities since its founding by noting its
support for solvency/capital lending programs
under wartime V-loan authority that it adopted
on April 6, 1942, and revised on September 26,
1950 (Board Annual Report 1942, 89-91; 1950,
72-74). Federal Reserve Banks w ere authorized
to act on behalf o f the guaranteeing agencies
(War Department, Navy Department, etc.) as fis­
cal agents o f the United States, meaning, the
Treasury was required to reimburse them for
their outlays. In acting as a guarantor o f defense
production loans, the Federal Reserve provided
a model o f guaranteeing authority that was
later invoked w hen bailouts o f peacetime enter­
prises w ere proposed in the 1970s. Those de­
velopments and Federal Reserve lending since
the 1980s to institutions with a high probability
o f insolvency in the near term represent a
major departure from its historic mandate to
provide loans to illiquid but not insolvent
depository institutions. In the section that fol­
lows I discuss the apparent change in how the
Federal Reserve regards its mandate.

2 . ASSISTANCE T O INSOLVEMENT
NONBANKS AN D BANKS SINCE
THE 1 9 7 0 s

A. Assistance to Insolvent
Nonbanhs
An appropriate starting point is the official
response to financial problems o f the Penn Cen­
tral Railroad that surfaced in 1970. Though it
did not lead to discount w indow assistance,
nonetheless it reveals clearly the pressures that
w ere to lead to such a practice. The Nixon Ad­
ministration proposed to give the com pany a Vloan as a bailout. However, for the loan to be of
any use, legislative approval was required, since
guarantees o f loans for defense production were

http://fraser.stlouisfed.org/
FEDERAL RESERVE BANK OF ST. LOUIS
Federal Reserve Bank of St. Louis

to expire on June 30. W hen legislation stalled in
Congress, the Administration requested the Fed­
eral Reserve Board to authorize the Federal
Reserve Bank o f New York to give the company
discount w indow assistance. The request was
rejected and, as a result, the com pany filed for
bankruptcy on June 21, 1970. On June 30, Con­
gress approved a Joint Resolution, extending the
Defense Production Act but limiting the maxi­
mum obligation o f any guaranteeing agency (for
example, the Federal Reserve) to $20 million,
and stipulating that "The authority conferred by
this section shall not be used primarily to pre­
vent the financial insolvency or bankruptcy o f
any person, unless" the President certifies “a
direct and substantially adverse effect upon
defense production" (Federal Reserve Bulletin
1970, 720).
If the incident had ended at this point, it
would have been rem em bered primarily as a
political dispute between the Administration and
the Congress. Penn Central’s bankruptcy would
have been regarded simply as the key to the
restructuring o f its operations. Instead, the Fed­
eral Reserve reacted as though the com pany’s
default on $82 million o f commercial paper it
had outstanding w ould generate a financial cri­
sis. The Federal Reserve assumed that lenders
w ould not discriminate between a troubled issuer
and other perfectly sound issuers o f commercial
paper, so that the latter would be unable to roll
over their issues. "It was made clear that the
Federal Reserve discount w indow w ould be
available to assist banks in meeting the needs of
businesses unable to roll over maturing com ­
mercial paper” (Board Annual Report 1970, 18).
However, commercial paper issuers that faced
difficulties did so not because o f the condition
o f the market as such, but because o f condi­
tions peculiar to themselves (for example, Chrys­
ler Financial and Commercial Credit) (Carron
1982, 398). The fully justified verdict o f the
1971 Economic Report o f the President (69) was
that no "genuine liquidity crisis existed in
mid-1970."
The Penn Central episode fostered the view
that bankruptcy proceedings by a large firm
created a financial crisis, and that, if possible,
bankruptcy should be prevented by loans and
loan guarantees; the "too big to fail” doctrine in
embryo.
The financial difficulties faced by New York
City in 1975 led the Federal Reserve to inform

63

Congress o f its response to suggestions that it
might serve as a source o f em ergency credit.
Governor George W. Mitchell cautioned “against
any proposals that would provide direct access
to central bank credit by hard-pressed govern­
mental units" (Federal Reserve Bulletin 1975, 410).
Chairman Arthur F. Burns reiterated that caution
and reported on contingency plans to increase
temporary discount w indow lending to com m er­
cial banks in the event o f a major municipal
default. However, he added that if a default ulti­
mately required "write-downs that could seri­
ously impair the capital o f some banks,” the
Federal Deposit Insurance Corporation, not the
Federal Reserve, had statutory pow ers to assist
federally insured banks that found their capital
impaired (Federal Reserve Bulletin 1975, 635-636).
In the end, Congress passed a law guaranteeing
New York City loans o f up to $2.3 billion in
1975, reduced to $1.65 billion in 1978, but the
Federal Reserve’s involvement in the rescue ar­
rangement was only limited fiscal agency serv­
ices.3 The Fed also acted as fiscal agent for
Treasury loan guarantees issued during the
bailouts o f the Lockheed (1971) and Chrysler
(1979) corporations.4
I have been unable to find any reference to
the Fed's involvement in these three loan guaran­
tees in any o f its publications. By consulting the
U.S. Code—a source for lawyers, not econ o­
mists—however, I have been able to ferret out
the details o f that involvement. My guess is that
the Fed was unwilling to publicize its role be­
cause it was not voluntary.
The most recent attempt to use the discount
w indow to assist a nonbank involved the FDIC.
In March 1991, the FDIC chairman, William
Seidman, requested Congressional authorization
for a direct loan o f $25 billion by the Federal
Reserve to the Bank Insurance Fund. Chairman
Alan Greenspan, testifying before the Senate
Banking Committee the next month, opposed
such a loan. That did not deter Treasury Under
Secretary for Domestic Finance Robert Glauber
from renewing the request in testimony on May
29, 1991, before a subcommittee o f the House
Ways and Means Committee. The Federal
Reserve’s required subscription to the FDIC on
its establishment in his view served as a prece­
dent. The FDIC recapitalization and banking re­
form bill that the Treasury prepared included
3See U.S. Code (1975, 1978).




provisions authorizing the FDIC to borrow $25
billion from the Federal Reserve Banks and
amending section 13 o f the Federal Reserve Act,
authorizing any Federal Reserve Bank "to make
advances to the Federal Deposit Insurance Cor­
poration, upon its request” (Treasury bill 1991,
sec. 402, 245). The July 23, 1991, bill prepared
by the House Committee on Banking, Finance
and Urban Affairs did not include those provi­
sions (H.R.6, 102nd Cong., 1st sess.). The final
legislation, the FDIC Improvement Act o f 1991,
follows the House bill in increasing from $5 bil­
lion to $30 billion the FDIC’s authority to b o r­
row directly from the Treasury, not from the
Fed.
Despite the restraint in the Act with respect
to recapitalizing the FDIC, restraint is absent
from another provision. The Act amended Sec­
tion 13 o f the Federal Reserve Act that deals
with the Federal Reserve’s authority to discount
for nonbanks. The amendment eliminated the
requirement that the notes, drafts or bills ten­
dered by nonbanks be eligible for discount by
member banks. As interpreted by Sullivan &
Cromwell, a New York law firm, for its clients
in a memorandum o f Decem ber 2, 1991, this
provision enables the Fed to lend directly to
security firms in em ergency situations. Tradi­
tionally, commercial banks, knowing they had
access to the discount w indow, have lent to
brokerage firms and others short o f cash in a
stock market crash. It is not clear w hy the
traditional practice was deemed unsatisfactory.
In my view, the provision in the FDIC Improve­
ment Act o f 1991 portends expanded misuse o f
the discount window.
To this date, the Fed has apparently been a
reluctant participant in loans and loan guaran­
tees to nonbanks. The question must be asked
whether it will be firm in the future in resisting
pressures to fund insolvent firms that are politi­
cally well-connected.

B. Assistance to CAMEL 4- and
5-Rated Banks
In 1974 the Federal Reserve behaved contrary
to traditional principles when uninsured deposi­
tors started a run on the Franklin National Bank
after news surfaced that it had large foreign ex­
change losses.The Comptroller o f the Currency
did not close it promptly. The decision o f the
“See U.S. Code (1971) for Lockheed and U.S. Code (1980)
for Chrysler.

SEPTEMBER/OCTOBER 1992

64

regulators was that the Federal Reserve discount
window, starting in May, would provide loans
until the FDIC found a purchaser o f the failed
institution. Over the next five months, the Fed­
eral Reserve Bank o f New York lent continuous­
ly to Franklin; the maximum amount lent, on
October 7, 1974, was $1.75 billion, representing
nearly one-half o f Franklin’s assets. On October
8, the bank was declared insolvent and taken
over by a foreign consortium.
Among the precedents established by discount
w indow lending to Franklin National was that
its London branch assets w ere accepted as col­
lateral, and that, for the first time, the b orrow ­
ings covered withdrawals from the London
branch as well as Franklin's domestic branches.
Although, on one hand, Franklin National simply
borrow ed at the discount rate, what was un­
usual in this episode was that in September
1974 the Federal Reserve assumed responsibility
to execute Franklin’s existing foreign exchange
contracts, since bidders for the bank w ere un­
willing to honor them. It also agreed to extend
discount w indow assistance, if needed, to the
purchasing bank. The FDIC, m oreover, did not
immediately repay the discount w indow loan—
its normal practice—but signed a three-year
note obligating itself to do so as the collateral
Franklin supplied was liquidated. In effect, the
Federal Reserve lent capital funds that the in­
surance agency contributed to the purchasing
bank. The interest cost to the Fed o f subsidizing
loans to Franklin has been estimated at $20 mil­
lion (Garcia and Plautz 1988, 228). In executing
Franklin ’s foreign exchange contracts, the Fed
also incurred opportunity costs o f staff time and
lost interest on part o f its portfolio.
The rescue o f Franklin National Bank shifted
discount w indow use from short-term liquidity
assistance to long-term support o f an insolvent
institution pending final resolution o f its prob­
lems. The bank was insolvent when its b orrow ­
ing began and insolvent when its borrow ing
ended. The loans merely replaced funds that
depositors withdrew, the inflow from the
Reserve Bank matching withdrawals.
The undeclared insolvency o f Continental Il­
linois in 1984 was also papered over by exten­
sive discount w indow lending from May 1984 to
February 1985, albeit with smaller subsidies
than in the case o f Franklin National—an amend­
ment to Regulation A as o f September 25, 1974,
permitted application o f a special rate on em er­
gency credit after eight weeks that was closer

FEDERAL RESERVE BANK OF ST. LOUIS


to a market rate. The borrow ing covering Con­
tinental’s holding com pany as well as the bank
at some dates amounted to as m uch as $8 billion.
Again the FDIC assumed the bank’s loan, which
it eventually repaid from the proceeds o f liq­
uidating the bank’s assets, concluding with one
large $2.1 billion payment in September 1989—
an enormous cash drain.
The discount w indow has been valued by the
Federal Reserve as a mechanism for directing
funds to an individual bank with liquidity
problems. It regarded its loans to Franklin Na­
tional and Continental Illinois as exceptional o c­
currences. However, when hundreds o f CAMEL
4- and 5-rated banks, as noted at the beginning
o f this paper, w ere receiving extended accom ­
modation even though they faced a high proba­
bility o f near-term failure, discounting can no
longer be regarded simply as a means o f provid­
ing temporary liquidity. What explains this
transformation in practice?

C. Why the Departure From the
Historic Norm o f Discount Window
Use?
In the United States, with federal spending
budgeted at an all-time high, policy makers see
the discount w indow as a mechanism for
providing funds o ff budget. Legislation is neces­
sary to authorize the Fed to provide assistance
to favored nonbanks, so the use o f the window
isn't kept secret, but it may seem a cost-free
way o f funding them because repayment can be
rolled forw ard indefinitely. This may explain
the recent spate o f efforts to use discount win­
dow assistance fo r nonbanks.
With respect to loans to banks with a high
probability o f insolvency in the near term, it is
noteworthy that in 1974 only four banks failed.
By the late 1980s, failures w ere num bered in
triple digits, and the FDIC’s problem banks, in
four digits. Having once set the precedent of
lending to such problem institutions, at least
tw o explanations may account for this practice
by the Federal Reserve: (1) As in the case of
Franklin and Continental Illinois Banks, its ac­
tions may have been taken at the bidding o f the
FDIC, or perhaps on its ow n initiative, in order
to mitigate the FDIC’s plight. (2) The Federal
Reserve may regard failure o f a large institution
as potentially triggering a financial collapse or a
run on the dollar. Fear o f contagion may have
becom e the Federal Reserve’s overriding
concern.

65

Even if these explanations account for the
change in Federal Reserve discount window
practice, neither may justify the change. Before
dealing with this issue, it is important to assess
the costs o f wholesale discount w indow lending
to insolvent institutions, to which I now turn.

3. COSTS OF LENDING T O INSOL­
VENT INSTITUTIONS
For the Fed to lend directly to the Treasury
or to government agencies that the Treasury
would otherwise fund through regular ap­
propriations is a slippery slope. The costs are
politicization o f the m oney supply process. The
Fed’s charter wisely prohibits such lending.
Discount w indow accommodation to insolvent
institutions, whether banks or nonbanks, misallocates resources. Political decisions substitute
for market decisions. Institutions that have
failed the market test o f viability should not be
supported by the Fed's m oney issues.
A depository institution traditionally was said
to be eligible for discount w indow assistance
when it was illiquid but solvent. In recent
years, it has been given assistance when it was
liquid but its insolvency was undeclared. On a
market value basis, an institution is insolvent
w hen assets are less than liabilities. Since book
values are the usual measure o f assets and lia­
bilities, the divergence between assets and liabil­
ities may only be revealed long after the market
value o f its assets has fallen below the market
value o f its liabilities. In addition, an institution
may be liquid but insolvent, so long as its cash
flow is positive.
A decision to declare an institution insolvent is
the prerogative o f the chartering agency: the
Comptroller o f the Currency for national banks,
state authorities for state-chartered banks su­
pervised by the Fed and the FDIC. The FDIC,
since 1989, however, can both rem ove deposit
insurance and substitute itself as receiver o f
state banks. It can force a state to close banks
and, as the thrift insurer, close insolvent in­
sured thrifts. (It does not have authority to
close credit unions.) If the chartering agency
has delayed closure, the Federal Reserve has
acted as if a troubled institution is entitled to
discount window assistance provided it can fur­
5lt was only extended credit borrowers that tailed in the data
the House Banking Committee obtained from the Fed in
1991. Banks that obtained seasonal credit at the win


nish acceptable collateral. The question I raise is
whether the Federal Reserve's position is defen­
sible when inferior CAMEL ratings provide in­
dependent evidence on the likelihood o f insol­
vency in the near or immediate future.
Since the Federal Reserve routinely sterilizes
discount w indow reserve infusions, does it
make any difference whether the reserves are
provided to solvent or insolvent banks or
whether the period for which the reserves are
provided is limited or extended? After all, if the
reserves w ere not made available through the
discount window, open market purchases would
add an equivalent reserve contribution to the
banking system.
I believe that it does make a difference
whether reserves are injected by open market
purchases or by discount window lending, espe­
cially if insolvent banks are permitted to b o r­
row for extended periods. Discount w indow
lending may not affect proposed monetary
growth, but it has other effects that make it an
undesirable source o f reserves.
Open market operations are anonymous. The
market allocates reserve injections or withdraw­
als among participants according to their rela­
tive size and current opportunities. Much
greater discretion is exercised by the Federal
Reserve in the allocation o f reserves through
discounting, since the Fed knows the institu­
tions that request discount accommodation. The
public learns about the magnitude o f both open
market operations and discount window credit
from the data the Federal Reserve publishes,
but it does not learn the names o f the banks
that received loans. The data made available to
the House Banking Committee in 1991 revealed
the names o f the institutions that had failed
despite extended discount w indow loans, but
not the names o f the few banks that had
received such loans but had not failed.5 The
secrecy may be good public policy, but it leaves
open the question whether provision o f loans
on a case-by-case basis assures equal treatment
for all. This is an argument against discount
w indow lending in general, not specifically to
insolvent banks, an argument that has often
been made in the past without reference to the
specific problem o f insolvent banks (for exam­
ple, Friedman 1960, 38).
dow did not fail. As footnote 2 on page 59 contends, the
discount window is not essential for this use.

SEPTEMBER/OCTOBER 1992

66

Since the 1970s, the Federal Reserve has ex­
tended long-term discount w indow assistance to
depository institutions that by objective stan­
dards w ere likely to fail. It has done so in the
belief that, in the absence o f such assistance,
contagious effects w ould spread from the trou­
bled institutions to sound ones. The belief is
particularly entrenched for large troubled inter­
mediaries, reflecting an apprehension that halt­
ing the operation o f such institutions would
have dire unsettling effects on financial mar­
kets. Before 1985, the goal o f such discount
w indow assistance was a restructuring o f the
problem institution as a viable entity with both
insured and uninsured deposits made whole.
That was the situation in 1984 when Con­
tinental Illinois was rescued. The implication
was that any other response w ould have
brought on contagion. Yet if the bank had been
closed before its net w orth turned negative, the
institutional depositors, foreign bank depositors
and creditors w ho ran on it might well have
redeposited their withdrawals elsewhere or
bought financial assets to replace the certificates
o f deposit Continental issued and that they
w ere no longer willing to buy. Even if some in­
terbank depositors that held as much as half
their equity in uninsured deposits at Continental
had obtained only a fraction o f their claims im­
mediately upon the closing, they would ulti­
mately have recovered the full nominal value of
their claims after liquidation of the bank.6 The
market would have known that the claimants
on Continental w ere not in jeopardy. Even if
closing Continental had led to runs on the fo r­
eign interbank depositors — ostensibly the rea­
son for keeping Continental in operation — the
lenders o f last resort in the nations concerned
could have provided adequate liquidity in their
markets to tide the banks over if the Continen­
tal deposits w ere their only problem. Fear of
contagion should not determine a regulator’s de­
cision to keep an insolvent bank open. It should
lead the Fed to lend to the market to prevent
the contagion.
If fear o f contagion is a lesson the Federal
Reserve has learned from the banking panics of
1930-33, it is the w rong lesson. Contagion then
occurred in an environment in w hich the Fed
6This assumes that the bank's value would have been real­
ized in a forced sale of assets.
H'he subsidized rate may have risen to take into account
rates on market sources of funds but it is still a subsidy

http://fraser.stlouisfed.org/
FEDERAL RESERVE BANK OF ST. LOUIS
Federal Reserve Bank of St. Louis

permitted the money supply to decline drastical­
ly, rendering banks insolvent not because o f
their ow n actions but simply because o f the col­
lapsing econom y. The right lesson is that con­
tagion need not arise if open market purchases
are made adequate both to reassure the market
and to prevent a collapse in the quantity o f
money. Examples are the Fed’s provision o f li­
quidity to cushion the econom y from the effects
o f the 1987 stock market crash and the collapse
o f Drexel Burnham.
Since 1985, prolonged discount w indow as­
sistance has generally terminated not with re­
structuring but with closure o f the insolvent
banks. W hen banks are known to be insolvent,
postponement o f recognition o f losses that have
occurred might well have increased current
losses. Uninsured depositors have m ore time to
withdraw their funds. The insurance agency,
which is to say the taxpayer, ultimately bears
any added costs o f delayed closure. By lending
to the banks in question, the Federal Reserve
encourages this practice. Absent regulatory re­
straints or incentives to the contrary, the policy
clearly encourages risk-taking and invites moral
hazard problems. If a bank with the least
desirable CAMEL rating can obtain subsidized
discount window assistance, that institution ob­
tains a competitive advantage over solvent ones
for as long as the Federal Reserve supports it.7
The Federal Reserve Banks decide whether
they will extend a loan on the basis o f collateral
that the would-be borrow ers offer. This deci­
sion is undoubtedly influenced by the condition
o f the insurance agency: w hether it has the
funds to pay o ff depositors and take over the
failing bank’s assets w hen it cannot arrange a
merger o f an insolvent bank with a solvent one
or arrange removal o f existing management by
placing an institution in receivership. The condi­
tion o f the insurance agency in turn is also af­
fected by a chartering agency’s forbearance or
prompt action in declaring the insolvency of
one o f its constituents. The Federal Reserve has
cooperated by extending long-term support to
an institution with a high probability o f failure
until a resolution o f its problems was arrived at.
Discount w indow lending to insolvent banks
might cease if, under the terms o f the FDIC Imcompared to what deposit brokers and other non-Fed
sources of funds would charge if the dying banks were left
to fend for themselves in the market.

67

provement Act o f 1991, the Fed no longer ad­
vanced funds to keep critically undercapitalized
institutions in operation, and the insurance
agency took prom pt corrective action to appoint
a receiver for those institutions.8

4. COULD REFORM REMEDY
W H A T ’S W R O N G W IT H THE DIS­
COUNT W IN D O W ?
W ould discontinuation o f Fed lending to insol­
vent banks establish the inviolability o f the dis­
count window? For many reasons that is not
the case.
Regardless o f one's attitude to discount win­
dow lending for seasonal and adjustment
purposes—the private sector could accommodate
those needs—many economists customarily as­
sign one indispensable function to the discount
window, namely, as lender o f last resort: The
Federal Reserve should use discounting in "ex­
ceptional circumstances" (in the w ords o f Regu­
lation A) to provide extended credit to solvent
institutions with liquidity problems.
However, the Federal Reserve does not need
the window to serve as a lender o f last resort.
The case against operation o f the discount win­
dow has rested on grounds that open market
operations are sufficient for the execution of
monetary policy in both ordinary and exception­
al circumstances, that individual banks that
need and can justify special assistance can
receive such assistance through the federal
funds market, and that discounting invites dis­
cretionary subsidies to banks favored by the
Fed (Goodfriend and King 1988, 216-53).
There is still another reason that the discount
w indow serves no useful purpose. A review of
the use o f the discount mechanism by the Fed­
eral Reserve since its founding demonstrates a
series o f misconceptions on its part about what
it can achieve by affording banks the opportuni­
ty to acquire b orrow ed reserves. The miscon­
ceptions have varied over time, depending on
the objectives the System pursued.
Let me note some o f the misconceptions:
(1) The Federal Reserve can determine whether
borrow ed reserves serve “productive” rather
than "speculative" use o f credit.

(2) Banks borrow only for "need” and not for
profit.
(3) The absolute level o f free reserves or b o r­
rowings indicates whether banks choose to
acquire or liquidate assets.
(4) The spread between discount rates and mar­
ket rates does not affect bank borrowing.
(5) The tradition against continuous borrow ing
is a satisfactory substitute for a penalty dis­
count rate.
(6) Borrowing by banks signals bank weakness.
(7) Little bank borrow ing signifies money mar­
ket ease.
(8) "Technical” adjustments may explain discount
rate changes, but their announcement con­
veys useful information to financial markets.
(9) Banks can be dissuaded from excessive use
o f the discount w indow by Reserve Bank ap­
peals and exhortations instead o f discount
rate increases.
Since the 1970s, the Federal Reserve has acted
on the belief that discount w indow assistance to
banks with a high probability o f insolvency in
the near term, especially large ones, will, by
delaying closure, eliminate contagious effects on
financial markets.
In practice, the Federal Reserve’s discount
w indow activities have created perverse incen­
tives, shifting risk from depositors to taxpayers.
If a threat o f systemic bank failures did arise,
the Fed should counter it by open market oper­
ations, rather than by assistance to individual
institutions. However, if the Federal Reserve
prevents serious declines in the money supply,
it is highly unlikely that the failure o f an in­
dividual bank, how ever large, would trigger sys­
temic bank failures.
Closing the discount w indow would free the
Fed not only from likely future misconceptions
but also from the recurrent pressures, to which
it has been subject since the New Deal, to ac­
commodate nonbanks, not to mention pressures
from the Treasury to fund government agencies
o ff budget.

5. CONCLUDING COMMENTS
I’ve surveyed the changes in Federal Reserve
discount w indow practices since the System’s
founding. Early on the System emphasized that

8For an alternative view of the possible consequences of a
prompt corrective action strategy, see R. Alton Gilbert
(1991).



SEPTEMBER/OCTOBER 1992

68

borrow ing was supposed to be limited to short­
term reserve needs. By the 1980s, hundreds o f
banks rated by regulators as having a high
probability o f failure in the near term and
which ultimately failed w ere receiving extended
accommodation at the discount window.
My reading o f this recent experience is that
the change in discount w indow practices, by
delaying closure o f failed institutions, increased
the losses the FDIC and ultimately taxpayers
bore.9 Recent legislation limits use o f the dis­
count w indow for long-term loans to troubled
banks. M ore important, it also provides that a
supervisory agency is to appoint a receiver for
an institution that falls below a critical capital
ratio, curtailing the regulator's discretion
regarding when to intervene in the case o f an
undercapitalized bank.
These changes, even if implemented—it is not
yet know n whether they will be—do not sanctify
the continued operation o f the discount window.
Individual banks that need assistance, if credit­
worthy, can obtain loans without subsidies from
the federal funds market. The Fed can be an ef­
fective lender o f last resort if restricted to open
market operations. In administering the discount
window, the Fed has been prone to mistake the
9My conclusion from reading the 1991 Senate and House
hearings on the long-delayed closings of the Bank of New
England and Madison National Bank is that delay in­
creased resolution costs. The condition of the institutions
deteriorated as the Fed continued to lend to them — they
were already rated CAMEL 5 when the continuous loans
began. With the value of liabilities greater than of earning
assets in these institutions, the gap grew as interest in­
curred on liabilities exceeded earnings on assets.
Delay, moreover, allowed outflows of uninsured deposits.
Had the institutions been closed promptly, the earnings
deficiency could have been offset at least somewhat by
reducing the principal paid to uninsured depositors. Even
so, at the closing, Bank of New England held $2.3 billion
in uninsured deposits, of which $1.25 billion were brokered.
At their peak, Fed advances amounted to $2.26 billion. The
FDIC’s loss was $2.5 billion. As L. William Seidman testi­
fied, the FDIC decided to protect all depositors of the Bank
of New England, at “ the additional cost [of] somewhere in
the $200 to $300 million range up front” (see his statement
in Senate Hearings on the failure of the Bank of New En­
gland, pp. 25-26).
In the absence of Fed lending to a bankrupt institution,
early closing would have prevented a flight of uninsured
deposits. In effect, Fed lending merely replaced withdraw­
als of uninsured deposits. Before it was declared insolvent,
the Fed had lent the Madison National Bank $125 million,
which kept the bank open to permit withdrawals of $108
million in uninsured deposits. The FDIC’s final loss was
$156 million.
The FDIC suffers losses not only in cases in which it liq­
uidates failed banks but also in cases in which it arranges
some form of purchase and assumption. When it liquidates
a failed bank, the FDIC pays depositors the face value of
their claims and suffers a reduction in its reserves meas
http://fraser.stlouisfed.org/
FEDERAL RESERVE BANK OF ST. LOUIS
Federal Reserve Bank of St. Louis

effects o f its actions. These mistakes have
marred its execution o f monetary policy.
Without a discount window, the Fed will
avoid pressures to lend o ff budget to nonbanks
and to government agencies, which should be
funded through regular appropriations. Without
the distraction o f monitoring collateral and
deciding which bank applicants qualified for
assistance, it can concentrate its energies on
open market operations, the single instrument it
needs to control the quantity o f money. Without
a discount window, there will be no announce­
ment effects since the Fed will not have to set
the discount rate. That should dispel the im­
pression that it controls market interest rates.
A Federal Reserve System without the discount
w indow would be a better functioning institution.

REFERENCES
Board of Governors of the Federal Reserve System. Annual
Report (Washington, D.C., selected years).
Economic Report of the President (Washington, D.C., 1971).
Federal Deposit Insurance Corporation Improvement Act of
1991.
Federal Reserve Bulletin (Washington, D.C., selected years
and months).
ured by the full difference between book and current
values of the assets that support the deposits. When it ar­
ranges a purchase and assumption, it transfers the
deposits to the buyer and, depending on the purchase
price it has accepted, the FDIC is responsible for the re­
maining difference between book and current values of as­
sets that support the deposits transferred.
In my opinion, delay in recognizing losses that already
exist cannot be justified by the claim that the FDIC uses
the time to improve the behavior of the bankrupt institu­
tion, even if it were true that supervisors would be suc­
cessful at this late date in the institution’s history in
reforming it. Delay may, however, be helpful to the FDIC’s
public image by postponing a publicly disclosed decline in
the stated value of the reserves in the fund. That may be
the real reason the FDIC welcomes delay.
The FDIC has stated that the value of a bank to potential
bidders goes down when it is already involved in resolving
a failed bank case, as if that would validate delay. In fact,
it is the difference between book and market value of a
bank’s assets which a potential bidder learns that accounts
for any decline in the bank’s value, not the fact that an ef­
fort at resolution is under way.
What needs to be explained is why the Fed is the lender
and not the FDIC, which has had the authority since 1982
to lend to open bankrupt banks and since 1989 to conser­
vators. Some buyers might argue that assets are worth
more if FDIC can step in after it has fixed a price in a pur­
chase and assumption transaction and abrogates contracts
the institution has with third parties, e.g., for rent, utilities,
etc. That would be harder to do legally if the FDIC already
controlled the bank or had an outstanding loan to it. That
is not an argument that should encourage the Fed to lend
instead of the FDIC.

69

Friedman, Milton. A Program for Monetary Stability. The Millar
Lectures. Number Three (Fordham University Press, 1960).
Garcia, Gillian and Elizabeth Plautz. The Federal Reserve:
Lender of Last Resort (Ballinger, 1988).
Gilbert, R. Alton. “ Supervision of Undercapitalized Banks: Is
There a Case for Change?” this Review (May/June 1991),
pp.16-30.
Goodfriend, Marvin and Robert G. King. “ Financial Deregula­
tion, Monetary Policy and Central Banking,” in W.S. Haraf
and R.M. Kushmeider (eds.) Restructuring Banking & Finan­
cial Services in America (American Enterprise Institute,
1988).

_______ New York City Seasonal Financing Act of 1975.
Formerly enacted (now omitted from Code) as 31 United
States Code Sections 1501-1510. Public Law 94-143; 89
Stat. 797 (Dec. 9, 1975), pp. 797-99; Legislative History, p.
1509.
_______ New York City Loan Guarantee Act of August 8,
1978. Formerly enacted as 31 United States Code Sections
1521-1531; see note under 31 U.S.C. Section 6702. Public
Law No. 95-339.
_______ Chrysler Corporation Loan Guarantee Act of 1979.
15 United States Code Sections 1861-1875. Public Law
96-185;85 Stat. 1324 (January 7, 1980), pp. 1324-37.

Hackley, Howard. Lending Functions of the Federal Reserve
Banks: A History (Board of Governors of the Federal
Reserve System, 1973).

U.S. House of Representatives, Committee on Banking,
Finance and Urban Affairs, Staff. “An Analysis of Federal
Reserve Discount Window Loans to Failed Institutions”
(Processed, 1991).

Kaufman, George. “ Lender of Last Resort: A Contemporary
Perspective,” Journal of Financial Services Research, Vol. 5
(1991), pp. 95-110.

U.S. House of Representatives, Committee on Banking,
Finance and Urban Affairs. A Bill to Reform the Deposit In­
surance System ... and For Other Purposes (1991).

Shull, Bernard. “ Report on Research Undertaken in Connec­
tion With a System Study,” in Reappraisal of the Federal
Reserve Discount Mechanism, Vol. 1 (Board of Governors
of the Federal Reserve System, 1971), pp. 27-76.

_______ . Failure of Madison National Bank, Hearing, 102nd
Cong. 1st sess., Serial No. 102-38 (Government Printing
Office, May 31, 1991).

Smead, Edward L. “ Operations of the Reserve Banks,” in
Banking Studies (Board of Governors of the Federal
Reserve System, 1941), pp. 249-70.
Todd, Walker F. “ Lessons of the Past and Prospects for the
Future in Lender of Last Resort Theory,” Federal Reserve
Bank of Cleveland Working Paper 8805 (1988).
U.S. Code. Emergency Loan Guarantee Act. 15 United States
Code Sections 1841-1852. Public Law 92-70; 85 Stat.
178-182 (August 9, 1971), pp. 193-98; Legislative History, pp.
1270-78.




_______ The Failure of the Bank of New England Corporation
and Its Affiliate Banks, Hearing, 102nd Cong. 1st sess.,
Serial No. 102-49 (Government Printing Office, June 13,
1991).
U.S. Senate, Committee on Banking, Housing, and Urban Af­
fairs. The Failure of the Bank of New England, Hearings,
102nd Cong. 1st sess., Serial No. 102-354 (Government
Printing Office, January 9, May 6, and September 19,
1991).
U.S. Treasury Department, Capital Markets Legislation Office.
“A Bill to Reform the Federal Deposit Insurance System ...
and for Other Purposes: (Processed, 1991).

SEPTEMBER/OCTOBER 1992

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Post Office Box 442
St. Louis, Missouri 63166

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