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May/June 1992
Volume 77, Number 3

Federal Reserve
Bank of Atlanta

In This Issue:
Facing Up to Our Ignorance
About Measuring Monetary
Policy Effects
^Exchange Rate Variability
And International Trade
Commercial Bank Profitability
i?eview Essay



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Ispnomic
j^view
May/June 1992, Volume 77, N u m b e r 3

ramarne
• • •

Federal Reserve
Bank of Atlanta

President
R o b e r t P. Forrestal
S e n i o r Vice President a n d
D i r e c t o r of R e s e a r c h
Sheila L. T s c h i n k e l
Vice P r e s i d e n t a n d
A s s o c i a t e D i r e c t o r of R e s e a r c h
B. Frank K i n g

Research Department
William Curt Hunter, Vice President, Basic Research
Mary Susan Rosenbaum, Vice President, Macropolicy
Thomas J. Cunningham, Research Officer, Regional
William Roberds, Research Officer, Macropolicy
Larry D. Wall, Research Officer, Financial

Public A f f a i r s
Bobbie H. McCrackin, Vice President
Joycelyn T. Woolfolk, Editor
Lynn H. Foley, Managing Editor
Carole L. Starkey, Graphics
Ellen Arth, Circulation

• • • • H H H ^
The Economic Review of the Federal Reserve Bank of Atlanta presents analysis of economic
and financial topics relevant to Federal Reserve policy. In a format accessible to the nonspecialist, the publication reflects the work of the Research Department. It is edited, designed, produced, and distributed through the Public Affairs Department.
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information. ISSN 0732-1813




(Contents
May/June 1992. Volume 77. Number 3

Facing Up to Our
Ignorance about Measuring
Monetary Policy Effects
Eric M. Leeper

| y

E x c h a n g e Rate Variability
And International Trade
Vikram Kumar a n d
J o s e p h A. Whitt, Jr.

33

FYI—Commercial
Bank
Profitability Rises as
Interest Margins a n d
Securities Sales Increase

An understanding of the liquidity effect—the short-run lowering
of the interest rate when the money supply is increased—may provide clues to relationships between controllable economic variables
and others that policymakers would like to influence. To explore
various ways of quantifying the liquidity effect, this study characterizes the relationship between the federal funds rate and the monetary
base over the 1954-91 period. This relationship proved unstable during four subperiods commonly viewed as reflecting different policy
environments, raising questions about which economic behavior induces correlations of money and interest rates. The article's findings
point out the economics profession's woeful ignorance about the
short-run effects of monetary policy and highlight the need to go beyond simple correlations when identifying these effects.

The growth rate of international trade among major industrialized
countries has slowed during the past twenty years, and at the same
time exchange rate variability has increased. Investigating a possible
relationship between the two phenomena, the authors find that the
move to flexible exchange rates in 1973 may have added variability
and uncertainty to monetary and fiscal policy, which are major influences on market-determined exchange rates. Evidence concerning the
depressing effect of exchange rate variability on international trade
leads the authors to conclude that, although there probably is a harmful effect on economic welfare, it is not large enough to make reducing exchange rate variability a top priority of the world community.

Robert E. Goudreau

As interest rates fell in 1991 commercial banks of all sizes earned
higher adjusted net interest margins and profited from increased investment securities sales. This article highlights some of the more
interesting patterns of commercial banks' performance in both the
nation and the Southeast last year. Extensive tables provide details
about bank profitability from 1987 through 1991.

Review Essay

Edge

William Roberds



City: Life on the New

by Joël Garreau

F routier




¿Pacing Up to Our
Ignorance about
Measuring Monetary
Policy Effects
Eric M. Leeper

71
/ W acroeconomists have a reputation for disagreeing about al/ I
/ M
most everything. Deserved or not, that reputation encourages
/ I
/
m
decisionmakers to view economists' advice and predictions
/
^ ^
m
with skepticism. The disagreements among economists
• ! •
r
- J L
stem in large part from differences of opinion about the
economic behavior underlying observed data, differences that can be resolved only through economic research explicitly demonstrating the linkage
of movements in economic variables with the actions of specific players in
the economy. Such efforts to build a consensus make economists' predictions more credible and thus more useful to decisionmakers.
One important phenomenon on which there is widespread agreement,
however, is that an increase in the money supply lowers the interest rate in
the short run. This "liquidity effect" plays a central role in popular, political, and academic discussions of monetary policy. Casual discussions
that equate "high" interest rates with "tight" monetary policy implicitly assume that the liquidity effect exists. 1
The author is a senior
economist in the macropolicy
section of the Atlanta Fed's
research department. The
article draws heavily on
published work by the author
and David B. Gordon (1992).
The author thanks Tom Cunningham, Marco
Espinosa,
MaryClaire King, Mary
Rosenbaum, and Sheila
Tschinkel for helpful
comments.

Federal
Reserve B a n k of Atlanta



The liquidity effect is important because it is the channel through which
monetary policy affects the economic conditions that policymakers want to
influence. Although the Federal Reserve ultimately wants to influence such
things as output and inflation, it cannot control these variables directly.
However, over time horizons that are relevant for policy, the Fed can directly control a monetary measure that appears on its balance sheet. At the
same time, there is strong evidence that interest rates are correlated with future movements in output and prices. The liquidity effect, therefore, is the
nexus between what the Fed can influence directly and what the Fed ultimately seeks to influence. The goal of current empirical research on the liquidity effect is to establish stable relationships between a monetary measure

EconomicReuieiv7

and interest rates and between interest rates and other
variables in the hopes of finding stable relationships
between a controllable variable and the variables that
monetary p o l i c y m a k e r s want to influence. Unders t a n d i n g the r e l a t i o n s h i p b e t w e e n m o n e y g r o w t h
and the interest rate is important for practical policymaking.
The economic profession's consensus that the liquidity effect exists can be seen in the many theoretical
analyses that build in the liquidity effect as the first
step in the process for transmitting monetary policy effects to the rest of the economy. The liquidity effect is
a critical element in traditional Keynesian models
(based on James Tobin's 1947 work) and in the monetarist a p p r o a c h e s of Milton F r i e d m a n ( 1 9 6 8 ) and
Phillip Cagan (1972). Recent neoclassical models (for
example, Robert E. Lucas, Jr. 1990 and Timothy S.
Fuerst 1992) have included the liquidity effect to remedy the apparent deficiency of earlier neoclassical
models in which monetary expansions tend, if anything, to raise the nominal interest rate. 2
Although most economists believe that the liquidity
effect exists, the profession is far from a consensus on
a way to measure the effects of monetary policy on the
interest rate. The disagreements arise mostly because
empirical work on the liquidity effect has traditionally
made incredible assumptions about both private and
policy behavior. Without first specifying plausible behavior, it is impossible to make credible predictions of
the effects of policy.
This article reinterprets the traditional empirical
work and explores various ways to quantify the liquidity effect by presenting a largely atheoretical characterization of the relationship between the federal funds
rate (a short-term interest rate) and the monetary base
(currency in circulation plus bank reserves) over the
1954-91 period. 3 For much of this period, the Fed targeted the federal funds rate by conducting open market purchases and sales of U.S. Treasury securities.
These open market operations affected the amount of
reserves the Fed provided to the banking system,
thereby affecting the monetary base. Thus, although
the Fed has never targeted the monetary base per se, it
achieves its targeted level of the federal funds rate
through open market operations that necessarily influence the base.
The article also considers whether the relationship
between the funds rate and the monetary base is stable
over four subperiods that are commonly viewed as reflecting different policy environments. The research
replicates the pattern of correlations traditionally interpreted as evidence of the liquidity effect and shows

2

Economic Review




that this pattern is sensitive to which variables are held
fixed when the correlations are calculated. For example, when lagged interest rates, consumer prices, and
industrial production are held fixed, as the traditional
theory of the liquidity effect suggests they should be,
all evidence of the liquidity effect disappears: the
correlation between unexpected changes in money
growth and the interest rate is zero or positive. 4 In addition, the study finds that the relationships between
the f u n d s rate and the monetary base are unstable,
changing sign and size across the four subperiods considered.
These results lead to one of two possible conclusions: either the widespread belief in the existence of
the liquidity effect is incorrect, or the observed shortrun correlations between money growth and the interest rate do not primarily reflect the liquidity effect.
The latter conclusion seems more likely. The traditional theoretical analysis of the liquidity effect is
based entirely on demand-side behavior. Using the
traditional analysis to interpret correlations requires
assuming that the data are dominated by money demanders' responses to changes in monetary policy. It
is more likely, however, that the correlations arise in
large part from the responses of monetary policy to
changes in economic conditions. The findings reported here underscore the need to separate money-supply
and money-demand behavior carefully when estimating and interpreting the effects of monetary policy on
the interest rate.
In addition to discussing the traditional theoretical
analysis of the liquidity effect and the money growth/interest rate correlations that the analysis implies, this article examines ways the analysis is used to interpret data.
The article defines what it means to "identify" economic behavior and uses the example of the liquidity effect
to show how failure to identify an economic model can
lead to misleading interpretations of the data. This discussion leads to a simple way to think about how to use
data to isolate the monetary policy shocks that generate
the liquidity effect. Finally, there is a description of the
data set used to characterize the liquidity effect and a report on the empirical results.
By raising questions about the nature of the relationship between money growth and the interest rate,
this article argues that the economics profession is
woefully ignorant about how to measure this most immediate and fundamental effect of monetary policy.
Without thoroughly understanding the liquidity effect,
the profession cannot claim to understand precisely
the effects of monetary policy on inflation, output, or
other economic variables.

.May/June 1992

The Traditional Analysis
of t h e Liquidity Effect
The traditional theoretical analysis of the liquidity
effect, as presented in Friedman (1968) or Cagan (1972),
abstracts from many real-world complications to focus
entirely on the behavior of money demanders. The
analysis implies that an increase in the rate of growth of
the money supply, holding income and prices constant
in the short run, causes the nominal interest rate to fall
(see the money market graph in Chart 1).
The theory assumes that
inflation-adjusted) money
short-term nominal interest
(or the level of transactions),

the demand for real (or
b a l a n c e s d e p e n d s on a
rate, R, and real income
y:

Ml_=Md{Rnyt\

(1)

PI

where M d is the quantity of nominal balances demanded, p is the general price level, and Md/p is the demand
for real balances. The subscripts denote variables measured at date t. The nominal interest rate represents the
opportunity cost of holding money. As this opportuni-

ty cost rises, demanders will substitute out of money
and into assets that earn the increasing rate of return,
decreasing the quantity of m o n e y d e m a n d e d . This
negative interest elasticity of money demand produces
the downward-sloping demand curve in Chart 1. Higher income boosts the transactions demand for money,
and demanders will want to hold more money at any
given interest rate, shifting the demand curve to the
right.
Drawing the supply of money, M'\ vertically implies
that the Fed does not adjust the money supply in response to changes in the interest rate. The traditional
theoretical analysis typically assumes that the Fed also
sets the money supply independently of the level of inc o m e and prices. These assumptions correspond to
treating monetary policy as exogenous, or unrelated to
prevailing economic conditions. Treating monetary
policy as exogenous amounts to assuming that changes
in the money supply are arbitrary and random.
Equilibrium in the money market occurs at the point
where demand and supply coincide: Md = Ms. In the
short run, because income and prices are treated as
fixed, the money market determines the equilibrium
levels of the money stock and the nominal interest rate.

Chart 1
The Money Market: Conceptual Experiment
Underlying the Liquidity Effect
N o m i n a l Interest

Federal
Reserve Bank of Atlanta



MSA

MSR

Economic Reuieiv

3

To generate the liquidity effect, consider the following exercise: The Fed conducts an open market
purchase of Treasury securities, increasing bank reserves. An open market purchase shifts the moneysupply curve outward from M [ to M*. In the short run
the nominal interest rate must fall to induce money demanders to slide down their stable demand curve from
point A to point B and hold the new higher level of
both nominal and real money balances. This response
of demanders produces the liquidity effect.
Eventually, actual (and expected) inflation will adjust to the higher growth rate of money, and bondholders will drive up the nominal interest rate to maintain
the premonetary expansion real return on bonds; the
long-run correlation between money growth and the
nominal interest rate is positive. 5 The long-run tendency for changes in money growth to be reflected in expected inflation, and, thus, the nominal interest rate, is
the "expected inflation effect." The negative interest
elasticity of money demand produces the liquidity effect in the short run, but in the long run the expected
inflation effect dominates the liquidity effect. Chart 2
graphs the path of the nominal interest rate that the traditional theoretical analysis predicts will follow a
monetary expansion. 6
In recent extensions of this theory, the sooner people
come to expect a monetary expansion, the sooner the
expected inflation effect begins to dominate the liquidity effect and the milder and briefer the decline in the
interest rate will become. The modern models associat-

4
Economic Review



ed with Lucas (1990) and Fuerst (1992) employ an extreme version of this logic: only unanticipated increases in the m o n e y s u p p l y can l o w e r i n t e r e s t r a t e s .
Anticipated changes in money growth immediately affect the expected inflation rate, driving up the nominal
interest rate and producing only the expected inflation
effect.
Many researchers have used the traditional theory
of the liquidity effect to interpret data. If the analysis
in Chart 1 completely described observed movements
in the nominal interest rate and money growth, the
two variables would be negatively correlated in the
short run and positively correlated in the long run.
Researchers such as Lawrence J. Christiano (1991)
and Christiano and Martin Eichenbaum (1991a) explicitly interpret the short-run correlations as reflecting the liquidity effects of monetary policy that Chart 1
depicts.
Other researchers regress the interest rate against
current and past monetary aggregates and interpret the
regression coefficients as measures of the effects of
monetary policy on interest rates (see, for example,
Cagan 1966, 1972; Cagan and Arthur Gandolfi 1969;
William E. Gibson 1970a, 1970b; and Michael Melvin
1983). Recent empirical work tries to isolate unanticipated changes in the money supply and traces out the
response of the interest rate to unanticipated monetary expansions (see John H. Cochrane 1989; Christiano and Eichenbaum 1991b; Vefa Tarhan 1991; and
Steven Strongin 1991).

Chart 2
Path of the Interest Rate
Following an Unanticipated Monetary Expansion

.May/June 1992

identifying Money-Demand and
Money-Supply Behavior
Because the traditional theory of the liquidity effect
holds many variables fixed, the correlations between
observed money growth and interest rates frequently
cannot be interpreted directly in terms of Chart 1. The
theory is entirely a demand-side story that relies on the
Fed's expanding the money supply for reasons that do
not simultaneously shift the m o n e y - d e m a n d curve.
With no explanation of why the Fed chooses its policy,
the traditional analysis provides no guidance about
when an observed change in the money supply corresponds to the supply shift depicted in Chart 1. When
researchers apply the traditional theory directly to interpret correlations, they implicitly assume that every
change in the money supply arises for reasons that do
not perturb the stable money-demand curve. In practice, however, the Fed frequently changes the money
supply in response to shocks that also shift money demand. When the variation in money-supply shocks is
not independent of money demand, simple statistical
methods cannot distinguish how much of the money
growth/interest rate correlation is owing to the liquidity effect and how much of the correlation arises from
the dependence of money supply and interest rates on
other variables. To sort out which empirical regularities should be explained by the liquidity effect and
which are products of the response of monetary policy
to economic conditions, econometricians seek to identify money-demand and money-supply behavior.
Identification is the stage at which theory meets data. In applied economics there is no controlled experim e n t , a l t h o u g h such an e x p e r i m e n t is implicit in
theoretical discussions. To try to m a k e data m o r e
closely c o n f o r m to the controlled e x p e r i m e n t s assumed by theory, econometricians make assumptions
about the economic behavior that generated the data.
These assumptions "control for" (or hold fixed) one
kind of behavior to focus attention on another kind of
behavior. Consequently, an observed correlation can
then be separated into its behavioral sources: some
movements of the data arise from decisions of demanders while others are produced by actions of suppliers.
Identification problems are endemic to empirical
work in macroeconomics. In the early 1980s a flurry
of work sought to determine whether the increased
federal government deficits produced by the Reagan
Administration's tax cuts would drive up interest rates.
Most theoretical models imply an affirmative answer.
Most empirical work concluded either that there was

Federal
Reserve Bank of Atlanta



no relationship or that higher deficits are associated
with lower interest rates. The perverse negative correlations arise from researchers' failure to control for the
fact that deficits are countercyclical and interest rates
are procyclical: during recessions government revenues automatically decline, and government expenditures automatically rise at the same time that interest
rates tend to fall. If such cyclical fluctuations are the
dominant source of movements in deficits and interest
rates, simple statistical methods will find that the two
variables are negatively correlated. Implicitly the empirical work equates all observed changes in deficits
with the conceptual experiment performed in theoretical models of fiscal policy. The researchers have not
plausibly identified the theoretical experiment in the
data, making the predictions about the interest rate effects of tax cuts unbelievable.
A simple extended example illustrates how failing
to separate money-demand and money-supply behavior
can lead to mistaken inferences about the liquidity effect. Suppose that the economy is hit by an oil price
shock like the one that occurred at the beginning of the
Persian Gulf War in August 1990. Chart 3 shows the
consequences for the money market of an oil price
shock. Higher oil prices increase the relative price of
energy, which is an input for producing a wide range of
goods and services. Producers respond to the higher oil
price by cutting back on employment and output. Income falls from j 0 to yv decreasing money demand
and shifting the money-demand curve from Md(R, >'0) • p
to M\R, y{) • p.
Consider three possible monetary policy responses
to the oil price hike and the resulting correlations between money growth and the interest rate. First, if the
Fed were to respond to the oil price shock by keeping
the money supply fixed at its initial level, MSA, the interest rate would have to fall from R { to RB to induce
money demanders to continue holding the existing
money stock. In this instance, lower interest rates are
associated with no change in the money stock, so the
correlation between the two variables is zero.
Second, the Fed could choose partial accommodation of the decline in money demand by making the
money supply shrink with income. An accommodating monetary policy response would shift the moneysupply curve from M* to Msc. The interest rate would
still fall (to Rc) but not by as much as if the Fed had
held the supply fixed. Now the decline in the interest
rate coincides with a decline in the money growth rate,
so the correlation is positive.
Third, if the Fed were concerned with trying to offset the deleterious employment and output effects of

Economic Reuieiv

5

Chart 3
Possible Monetary Policy Responses to an Oil Price Increase

T h e oil price increase reduces i n c o m e from yQ to yv

shifting m o n e y d e m a n d from Md(R,

y0) • p to Md(R,

y,) • p. T h e v a r i a b l e Ms

is the

initial m o n e y supply, M [ . is the m o n e y supply w h e n the Fed partially a c c o m m o d a t e s the decline in m o n e y d e m a n d , a n d M ' n is the m o n e y
supply w h e n the Fed tries to offset the d e c l i n e in the i n c o m e by expanding the m o n e y stock.

the oil price shock, it could instead expand the money
supply to M"d, driving the interest rate still lower to
RD. This policy response produces a negative correlation between money growth and the interest rate.
The example illustrates that, although assumptions
about private behavior remain the same in the three
policy scenarios (namely, that the interest elasticity of
money demand is negative), the resulting correlation
between money growth and the interest rate varies
with assumptions about policy behavior. The reason
for the result is straightforward: neither the increase
nor the decrease in the money supply in the last two
cases corresponds to the conceptual experiment underlying the liquidity effect in Chart 1. To deduce that the
different correlations arise from different policy behavior, it is necessary to dispense with simple correlations and control the experiment by making specific
assumptions about how the Fed responds to oil price
shocks.
The simple correlations experience an identity crisis because the correlations cannot help decompose

6

Economic Review




the ultimate decline in the interest rate into the amount
based on demanders' behavior and that resulting from
the supplier's behavior. Suppose that instead of relying
on simple correlations, a model that fully identified
the behavior underlying Chart 3 were constructed—
that is, estimates of how money demand depends on
the interest rate and income and how money supply
depends on income were available. Then the movement from the equilibrium at point ,4 to the equilibrium at point C, which arose when the Fed partially
accommodated the decline in money demand, could
be decomposed into two parts: (1) the increase in the
interest rate caused by moving from A to A' up the initial demand curve (the demand response to a shift in
supply) and (2) the decrease in the interest rate based
on moving from A ' to C on the new lower demand
curve (the interest rate response to a decline in income). T h e liquidity effect can then accurately be
identified as the negative correlation produced by demanders moving along their initial demand curve from
A to A'as the money supply contracts.

.May/June 1992

.Specifying Policy to Recover
the Liquidity Effect
To recover the liquidity effect of monetary policy, it
is not necessary to identify money-demand and moneysupply behavior completely, as in the example. If disturbances that shift the Ms curve but do not shift the
M d curve can be isolated—that is, if the monetary
policy shock is identified—it is possible to calculate
the resulting change in the interest rate and attribute
the full change in the interest rate to demanders sliding along a fixed demand curve. This approach has
been taken by many researchers recently (see, for example, Christopher A. Sims 1986, 1988; Christiano and
Eichenbaum 1991b; Strongin 1991; and Tarhan 1991).
Surprisingly, monetary theorists traditionally have
modeled monetary policy behavior as an arbitrary,
random process. This assumption is made implicitly in
empirical work by Cagan (1972), Cagan and Gandolfi
(1969), Gibson (1970a, 1970b), and Melvin (1983), to
name a few, and explicitly by Cochrane (1989), Christiano (1991), Christiano and Eichenbaum (1991a), and
Robert G. King (1991). In effect, these researchers
treat today's value of the money growth rate as the
outcome of the spin of a roulette wheel. 7
Any serious specification of monetary policy must
recognize that the Fed behaves purposefully. The Fed
tries to fulfill its congressional mandate to stabilize the
economy by making adjustments to the growth rate of
money based on a vast array of information. To the extent that the congressional mandate does not change
and the economic environment evolves only gradually,
the Fed's purposeful behavior will have a large systematic component. 8
Even if the Fed behaves purposefully and systematically, there will remain some aspect of policy choices
that cannot be predicted by private decisionmakers in
the economy. 9 The unpredictable part of policy choice
could arise from the fact that private agents are uncertain about the weights that members of the Federal
Open Market Committee will place on various monetary policy objectives when they vote on policy decisions. 10 The implication is that the Fed's choice of the
money supply can be modeled as depending on information the Fed knows at the time of the decision plus
a random error, which is revealed to private decisionmakers only at the time the policy choice is made.

time t, may include such things as the unemployment
rate, income, prices, interest rates, e x c h a n g e rates,
commodity prices, past monetary aggregates, and so
o n . " M \ » ) is a function that translates the information
into a systematic policy choice, and et is the aspect of
policy choice that appears to be random from the perspective of private agents. The policy shock e cannot
be predicted from past information, implying that, given information available today, the private sector's
best guess of e tomorrow is zero.
The specification of policy behavior in equation (2)
can be coupled with the money-demand behavior in
equation (1) to produce a new graph analogous to
Chart 1, except that the money-supply curve is no
longer vertical. For example, if the Fed increases the
money supply in response to increases in the interest
rate, the supply curve will be positively sloped. In addition, fluctuations in prices and income, which shift
the money-demand curve, may also shift the moneysupply curve if these variables are part of the information to which the Fed responds systematically—the Zr
By assumption, however, disturbances to e ; are shocks
that shift the supply curve for money but do not shift
the demand curve. Moreover, because the value of e is
unpredictable one period ahead, disturbances to e reflect unanticipated shifts in the money-supply curve. If
an econometrician can extract a time series of e's from
the data, she can conduct the controlled experiment in
Chart 1 by perturbing e and tracing out the resulting
path of the interest rate. All empirical work on the liquidity effect requires making some assumption about
how to extract the time series of e's from the data. 12

Data C o n s i d e r a t i o n s

(2)

The empirical part of this study evaluates the traditional interpretation of money growth/interest rate correlations as primarily reflecting the liquidity effect.
The work concentrates on relationships between the
monthly series for the monetary base and the federal
funds rate. The monetary base is chosen for two reasons. First, as the sum of two liabilities on the Fed's
balance sheet, the monetary base is closely associated
with the open market operations that underlie the liquidity effect. Second, the monetary base is a variable
over which the Fed can exert control, although the Fed
has chosen to passively supply some components of
the base, such as currency.' 3

The variable Z,, which summarizes the information
available when the Fed chooses the money supply at

In addition to its being the Fed's target variable during much of the 1954-91 period, there are two virtues

Mst = Ms(Zt)

Federal
Reserve Bank of Atlanta



+ et.

Economic Reuieiv

7

to using the federal funds rate. First, the funds rate is
extremely short term, a characteristic that helps separate liquidity effects from expected inflation effects
without imposing a theory of the term structure and
expected inflation. Second, for data at a monthly frequency interest rates with maturity structures longer
than one month would need to be converted to onemonth holding period returns (as, for example, Frederic S. Mishkin 1983 does).
Mimicking the theoretical liquidity experiment in
Chart 1 requires monthly data on the price level and
income. T h e c o n s u m e r price index is used for the
price level, and industrial production is used for income. As a gauge of manufacturing output, industrial
production clearly is not an ideal monthly measure of
income, but its use allows these results to be compared
with those from other empirical studies, which use industrial production as a proxy for income.
Some previous work found that the correlations between money growth and the interest rate change over
time. To investigate this possibility, the post-Korean
War period is subdivided into four nonoverlapping periods that reflect different policy environments: 1954:7
to 1972:12, 1973:1 to 1979:9, 1979:10to 1982:11, and
1982:12 to 1991:11. The relationships are also estimated over the full 1954:7 to 1991:11 period. Several
considerations guided the choice of subperiods. Marvin Goodfriend (1991) lists the 1950s, 1960s, and the
period since 1982 as times when the Fed indirectly targeted the f u n d s rate, suggesting from 1954 to 1972
and from 1982 to 1991 as subperiods. Melvin (1983)
writes of the "vanishing liquidity effect" after 1972,
when the United States moved to a flexible exchange
rate system. The early 1970s also saw the Fed gradually shift to targeting the funds rate tightly (see Timothy
Cook and Thomas Hahn 1989 and Goodfriend 1991),
leading to the choice of the 1973 to 1979 period. Finally, Cochrane (1989) shows the liquidity effect returns during the O c t o b e r 1979 to N o v e m b e r 1982
period when the Fed targeted nonborrowed reserves.

Estimation and Empirical Results
The data set and estimation techniques used in this
research can replicate the results from traditional regression analyses that have been interpreted as evidence
of the liquidity effect. In particular, an unanticipated
monetary expansion is followed by the path of interest
rates depicted in Chart 2. The traditional regressions,
however, impose strong and unrealistic restrictions on

8

Economic Review




the relationship between money growth and the interest
rate. When these restrictions are relaxed, all evidence
of the liquidity effect disappears.
Traditional Regressions with Exogenous Money
Growth. The traditional empirical approach to measuring the liquidity effect, associated with Cagan and
Gandolfi (1969) and others, estimates a relationship
between the interest rate and current and past money
growth rates: 14
rt = a + /30pl+plpt_l+...+Pnpt_n+Vt

(3)

n

j=o

where r is the level of the federal funds rate, p is the
growth rate of the monetary base, and 77 is a regression
error term. 15 Each of the /3 coefficients is an estimate
of the correlation between the federal funds rate and
money growth at some date. For example, (3Q reports
the correlation between the funds rate this month and
money growth this month, after controlling for the influence of past money growth rates on this month's
funds rate;
is the correlation between the funds rate
this month and m o n e y growth last month, holding
fixed the influence of current and more distant lags of
money growth. Leeper and Gordon (1992) report estimates of the /? coefficients from this regression that
closely resemble those found by earlier researchers.
Recent monetary theories emphasize that unanticipated changes in money growth produce the liquidity
effect while anticipated changes in m o n e y growth
produce only the expected inflation effect. To give the
traditional work a modern twist it is necessary to construct a time series of unanticipated changes in money
growth. In the spirit of the interpretations that Cagan
and others give to their traditional regression results,
this study initially m a i n t a i n s the a s s u m p t i o n that
money growth is exogenous so that an unanticipated
change in money is the change that cannot be predicted using past money growth rates. 16 Thus, appended to
equation (3) is a description of how money growth
evolves over time:
n

A =«50 + 2 > , P , +

(4)

T h i s e q u a t i o n a s s u m e s that the F e d ' s s y s t e m a t i c
choice of money growth today depends only on past
money growth rates. Much of the existing empirical
work on the liquidity effect implicitly treats this specification of money growth as a description of monetary policy behavior, so the Z variable in equation

May/June 1992

(2) includes only money growth rates for dates t — 1
and earlier. The variable er which is the part of policy
choice that the private sector cannot predict from past
information, is called an "innovation" to current money growth. To mimic the conceptual experiment in
Chart 1, this empirical work interprets perturbations in
et as shifts in the money-supply curve and uses equation (4) to produce a time path for money growth. The
path for money growth is fed into equation (3) to produce a predicted path of the interest rate.
Chart 4 reports the path of the federal funds rate
implied by estimating the econometric model in equations (3) and (4) during each of the sample periods.
The path shows how the interest rate moves for thirtysix months following a one-time unanticipated change
in the growth rate of the monetary base of one percentage point. When both dashed lines lie above (or
below) the zero axis, the interest rate is significantly
higher (or lower) than its value b e f o r e the m o n e y
growth innovation.
In Chart 4 monetary base innovations have a negative contemporaneous correlation with the funds rate
for all periods except the one from 1973 to 1979. The
path of the interest rate during the 1954-72 period
closely matches Friedman's (1968) traditional description of the effects of a monetary expansion, shown in
Chart 2. The average response shows that the funds
rate declines at impact and stays below its initial level
for nine months; three years after the innovation in the
money growth rate, the f u n d s rate is significantly
above its initial level.
Melvin's "vanishing liquidity effect" is the difference in the funds rate paths between the 1954-72 and
1973-79 periods. In the latter period, the funds rate response to a monetary base innovation is zero or positive over the full thirty-six-month horizon. Melvin
attributes this response to enhanced inflation sensitivity that led the expected inflation effect of a monetary
expansion to dominate the liquidity effect. As Cochrane
found, the funds rate response is sharply negative during the 1979-82 period, when an innovation in the
base is associated with a forty-basis-point decline in
the funds rate at impact. The interest rate is persistently lower in the 1982-91 period.
Chart 4 also underscores how misleading it may be
to estimate relationships over the full postwar sample.
Although the interest rate path for the 1954-91 period
is close to that described by Friedman, the path is an
average of very disparate patterns of responses over
the four subperiods.
Vector Autoregression with Exogenous Money
Growth. The estimation procedures underlying Chart 4

Federal
Reserve Bank of Atlanta



impose very strong assumptions about how the interest
rate and money growth rates are related. By relating
the interest rate only to current and past money growth
rates, equation (3) assumes that if other variables help
determine the interest rate, the other variables do so
only through their influence on the m o n e y supply.
Equation (4) assumes that only past growth rates of
the money supply help to predict the current growth
rate. More generally, equations (3) and (4) assume that
no other variables induce interest rates and m o n e y
growth to move together to generate the correlations
estimated in traditional regressions. 17
These strong assumptions are relaxed in two steps.
This section reports the results of assuming that past
values of other variables influence the interest rate in
ways that are independent of the money supply. In
keeping with the traditional theoretical analysis of the
liquidity effect, however, the m o n e y supply is assumed to be exogenous, depending only on its own
past. The next section allows other variables to help
predict the money growth rate.
The traditional theory depicted in Chart 1 involves
the price level and income, in addition to the money
supply and the interest rate. Recall that the conceptual
experiment that produces the liquidity effect requires
expanding the money supply and tracing out the response of the interest rate while holding prices and income fixed. Because equation (3) excludes all variables
except the rate of growth of money, there is no way to
be sure that prices and income are fixed in the empirical experiments reported in Chart 4.
Equation (3) is now modified by including past values of prices, income, and the interest rate along with
current and past money growth rates. The specification of exogenous money growth in equation (4) is
maintained. With income and prices now in the econometric model, it is also necessary to specify how they
respond to a monetary base innovation. The model assumes that income and prices depend in an unrestricted way on past values of all four variables. T h e s e
assumptions produce an econometric model called a
vector autoregression (VAR) with exogenous money
growth. With the estimated model in hand et is perturbed to generate a time path of the money growth
rate from equation (4). The three remaining equations
in the VAR produce time paths for the funds rate, income, and prices, using the generated path of money
growth as an input to the equations.
Chart 5 reports the responses of the funds rate to a 1
percent money growth innovation. 18 The contemporaneous correlation b e t w e e n unanticipated monetary
growth and the f u n d s rate is never negative and is

Economic Reuieiv

9

Chart 4
The Response of the Federal Funds Rate to a 1 Percent Monetary Base Innovation:
Traditional Regressions with Exogenous Money Growth

40
2 0

- -

- 6 0

- 8 0 -I
0

' '

,

3

• i i
6

9

12

15

18

21

24

3

6

9

12

15

18

21

24

• • i

•

• i •

. , ,

, , ,

, , ,

3

6

9

12

18

21

27

30

33

30

33

15 -,
10

- 1 0

-

-

1

-15
- 2 0

-

0

27

15

- 1 0

-15
-20

'

--

0

i

,
15

,
24

i i i i
27

30

33

Months following innovation in monetary base
The funds rate is measured in basis points. T h e solid line is the point estimate, and the dashed lines are significance bands (generated using
the Bayesian M o n t e C a r l o integration procedure described in D o a n 1990). The interest rate regressions w e r e estimated w i t h the following
lag lengths: 1954-72 (thirty-six lags), 1973-79 (eighteen lags), 1979-82 (six lags), 1982-91 (eighteen lags), a n d 1954-91 (thirty-six lags). The
zero month is the contemporaneous response of the funds rate.

10

Economic Review




M a y / J u n e 1992

Chart 5
The Response of the Federal Funds Rate to a 1 Percent Monetary Base Innovation:
Vector Autoregressions with Exogenous Money Growth

Months following innovation in monetary base
T h e funds rate is measured in basis points. T h e solid line is the point estimate, a n d the dashed lines are significance bands (generated using
the B a y e s i a n M o n t e Carlo integration procedure described in D o a n 1990). T h e vector autoregressions w e r e estimated w i t h the f o l l o w i n g lag
lengths: 1954-72 (twelve lags), 1973-79 (three lags), 1979-82 (three lags), 1982-91 (three lags), and 1954-91 (eighteen lags). The zero month
is the c o n t e m p o r a n e o u s response of the funds rate.


Federal
Reserve B a n k of Atlanta


Economic Review

11

Chart
4
The Response of the Federal Funds Rate to a 1 Percent Monetary Base Innovation:
Vector Autoregressions with Endogenous Money Growth

0

3

6

9

12

15

18

21

24

27

30

33

3

6

9

12

15

18

21

24

27

30

33

Months following innovation in monetary base

The funds rate is measured in basis points. T h e solid line is the point estimate, and the dashed lines are significance bands (generated using
the Bayesian M o n t e Carlo integration procedure described in D o a n 1990). The vector autoregressions w e r e estimated w i t h the following lag
lengths: 1954-72 (twelve lags), 1973-79 (three lags), 1979-82 (three lags), 1982-91 (three lags), a n d 1954-91 (eighteen lags). T h e zero month
is the c o n t e m p o r a n e o u s response of the funds rate.

Economic
12


Review

M a y / J u n e 1992

strongly positive in some subperiods. In most subperiods, the funds rate rises steadily following a money
growth innovation. Surprisingly, in the period from
1979 to 1982, during which the strongest contemporaneous liquidity effect showed up in Chart 4, the funds
rate response is positive. The only negative response
of interest rates is in the 1982-91 period after a lag of a
few months, but the response is not significantly different from zero.
The results in Chart 5 indicate that it is questionable
to interpret the traditional regression results as primarily reflecting the liquidity effect. When empirical work
controls for the influence of past interest rates, income,
and prices, as theory suggests it should, all evidence of
the liquidity effect disappears. If the traditional regression analyses were correctly specified and the results
primarily reflected the liquidity effect, then holding
other variables fixed should not alter the results.
Vector Autoregression with Endogenous Money
Growth. The work of Thomas J. Sargent (1976) and
Sims (1980) suggests that past interest rates are good
predictors of money. Leeper and Gordon (1992) find
that past interest rates, income, and prices jointly help
predict money growth in all periods except the one from
1973 to 1979 and that interest rates and income individually tend to be important predictors of money. This
section reestimates the VAR above but leaves the money growth equation unrestricted also, so the data determine the endogenous response of money growth to past
economic conditions. This approach specifies Z r in
equation (2) to include past values of all four variables,
so the money innovation e; is the change in the growth
rate that cannot be predicted using historical values of
money growth, the interest rate, income, and prices.' 9
Chart 6 reports the responses of the funds rate to a
money innovation. 20 Conditioning the money growth
innovation on additional variables d a m p e n s the responses of interest rates, but unanticipated monetary
expansions still fail to generate the liquidity effect. Allowing other variables to predict money growth does
not affect conclusions about the liquidity effect once
variables in addition to money growth rates are allowed to influence the interest rate directly. 21 The results suggest the need to move toward more careful
identification of monetary policy and private behavior.

S u m m a r y and Conclusions
There is broad agreement that the negative interest
elasticity of money demand is the economic mecha-

Federal Reserve Bank of Atlanta



nism that produces the liquidity effect. There is also a
widespread belief that the observed correlations between money growth and interest rates should be interpreted as the liquidity effect dominating the economy's
short-run response to monetary policy shocks. Given
this consensus, it is surprising that the data do not support explaining money/interest rate correlations entirely with the demand-side economic behavior described
by Friedman (1968) and Cagan (1972) and embedded
in models developed by Lucas (1990) and others.
The results of this study can be briefly summarized
as follows:
• The response of interest rates to a money growth
innovation frequently becomes positive and is
never negative when the correlations control for
the influence of past interest rates, money growth,
prices, and income.
• T h e signs and the patterns of correlations between money growth and interest rates are not
robust across subperiods of the 1954-91 sample.
• T h e findings reported here and in Leeper and
Gordon (1992) imply a statistical rejection of the
a s s u m p t i o n that m o n e y g r o w t h is e x o g e n o u s ,
which is critical to the traditional interpretations
of the data. The assumption of exogeneity is also
not sufficient to produce a negative correlation between unanticipated money and the interest rate.
When the interest rate, prices, and income are included in an unrestricted VAR, the correlation is
positive, independent of the assumption about the
exogeneity of money.
The evidence in this article raises questions about
which economic behavior induces money and interest
rates to move together. It is unlikely that analyses that
rely on an entirely demand-side story will be able to
explain the data. Although the economic behavior underlying the traditional analysis of the liquidity effect
seems quite plausible, the data are almost certainly
generated by more complicated behavior than that described in Chart 1. The demand-side mechanisms are
an incomplete description of the data in the absence of
identifying monetary policy behavior.
In the United States the identification problem is
actually more complicated than the extended example
in the text suggests. Money-demand and money-supply
decisions are inherently simultaneous at data frequencies of one month or longer. Demanders are choosing
a quantity of the monetary base to hold as a function
of the current federal funds rate, prices, and income,
as well as past i n f o r m a t i o n . T h e Fed supplies the

Economic Reuieiv

13

monetary base to hit a federal funds rate target during
this period. Even under the assumption that the Fed
does not observe current prices and income, the Fed
does observe a vast array of other information that
may serve effectively as proxies for current prices and
income. Thus it is extremely difficult to argue on a
priori grounds that there are readily available data series that shift money supply but do not shift money
demand and vice versa.
By not offering up a measure of the effect on the interest rate of a given open market operation, these results may appear exceedingly negative. Unfortunately,
the results accurately reflect the current state of eco-

nomic knowledge about the short-run effects of monetary policy. They also lead the way toward future research by pointing out the need to go beyond simple
correlations when identifying monetary policy effects.
R e c e n t w o r k s e p a r a t e s m o n e y - s u p p l y s h o c k s and
money-demand shocks by identifying vector autoregression models in a way that leaves the dynamics of
the model unrestricted (Sims 1986, 1988; Jordi Gali
1990). Interestingly, this approach tends to find liquidity effects from identified money-supply shocks. Only
by facing up to our ignorance about the effects of
monetary policy will future research help resolve the
uncertainty about the role of money in the economy.

Notes
1. Discussions of the liquidity effect often leave "the money
supply" undefined. Throughout this article "the money supply" refers to the monetary base.
2. In addition, many researchers seem to treat the liquidity effect as a criterion of acceptability in the specification, estimation, and simulation of economic models. For example,
Christiano (1991, 3) labels the negative short-run response
of interest rates to a surprise monetary expansion "a basic
premise guiding the implementation of monetary policy,"
which is an "important characteristic for a good model to
have." Bryant, Holtham, and Hooper (1988) report that all
but one of the dozen econometric models they study produce declines in short-term nominal interest rates following
a U.S. monetary expansion. Laidler writes, "Of the literally
hundreds of studies of the demand for money . . . I am aware
of only three that have failed to find a significant negative
relationship between the rate of interest and the demand for
money" (1985, 124).
3. Roberds (1992) discusses American monetary policy behavior during this period and presents evidence on federal
funds rate volatility from 1976 to 1991.
4. Similar results already exist. Mishkin (1983) fails to uncover a negative relationship between unanticipated money and
interest rates. Sims (1980, 1986) and Litterman and Weiss
(1985) report that unanticipated changes in the money supply are not associated with sizable short-run declines in interest rates.
5. The reasoning follows from the Fisher relationship, which
states roughly that the nominal interest rate equals the real
interest rate plus the expected inflation rate over the maturity of the instrument being priced. Implicit in the traditional
theoretical analysis is the assumption that monetary policy
cannot influence the real interest rate in the long run. See
Espinosa (1991) for a different perspective on this contentious issue in monetary theory.
6. Although the conceptual experiment in Chart 1 involves the
level of the money stock, empirical work frequently uses the

14

Economic Review




growth rate of money. This practice is less of an inconsistency than it may appear. The liquidity effect arises from
changes in the level of the money supply, while the expected inflation effect arises from changes in current and expected future growth rates of money. Of course, the level of
money today can be expressed in terms of current and past
growth rates and the level of money at some initial date. The
connection between levels and growth rates allows the two
measures to be used interchangeably. As a practical matter,
the empirical results presented later in the article hold
whether the money stock is in levels or growth rates.
7. T o be m o r e precise, this body of work often allows the
growth rate of money today to depend on past growth rates
plus the outcome of a spin of a roulette wheel today.
8. Roberds (1992) offers a clear presentation of interest rate
smoothing, one well-recognized proximate goal of monetary policy.
9. These arguments draw on Sims (1987).
10. Heller (1988), former member of the Board of Governors of
the Federal Reserve System, makes this point. After listing
several variables whose performance could bring forth a
discretionary open market operation, Heller writes, " F O M C
members often differ on the relative importance of these
factors" (428).
11. The Fed's behavior is couched in terms of the money supply
because, even when the Fed targets the federal funds rate, it
does so through open market operations that alter certain
monetary entries on the Fed's balance sheet.
12. As mentioned above, this claim says nothing about having
to extract analogous shocks to money demand to measure
the liquidity effect.
13. In contrast, many earlier articles on the liquidity effect use
broader monetary aggregates, such as M l or M2. Because
private behavior strongly influences these aggregates, the
Fed cannot control them under any operating procedure and
they are only loosely connected to the open market operations that the Fed conducts to achieve its target variable.

.May/June 1992

Leeper and Gordon (1991) report results that use M l and
M2 in place of the base.
14. Some studies regress the level of the interest rate against the
level of the money stock (Gibson 1970b and Stokes and
Neuburger 1979), some use the growth rate of money as the
independent variable (Cagan 1966; Gibson 1970a; Reichenstein 1987; and C o c h r a n e 1989), and some regress the
change in interest rates against the change in money growth
(Cagan and Gandolfi 1969; Cagan 1972; Gibson 1970a; and
Melvin 1983). This is not an exhaustive list of studies or
functional forms of the regressions that have been estimated.
15. The f o l l o w i n g lag lengths are used: 1954:7 to 1972:12
(thirty-six lags), 1973:1 to 1979:9 (eighteen lags), 1979:10
to 1982:11 (six lags), 1982:12 to 1991:11 (eighteen lags),
and 1954:7 to 1991:11 (thirty-six lags). These lag lengths
are consistent with those used in previous studies.
16. This specification of money growth denies any sort of purposeful monetary policy behavior. The specification is used
only because it is consistent with how the literature on the
liquidity effect has traditionally modeled money growth.
17. This is the thrust of Tobin's (1970) classic critique of evidence
in favor of monetarism (see, for example, Friedman and
Schwartz 1963a, 1963b and Friedman and Meiselman 1963).

18. These regressions estimate m o r e coefficients than does
equation (3), so the lag lengths were shortened as follows:
1954:7 to 1991:11 ( e i g h t e e n lags), 1954:7 to 1972:12
(twelve lags), 1973:1 to 1979:9 (three lags), 1979:10 to
1982:11 (three lags), and 1982:12 to 1991:11 (three lags).
The system for the 1979:10 to 1982:11 period includes only
past interest rates and money growth. Leeper and Gordon
(1991) show that the results do not change when different
lag lengths are used.
19. The new money growth specification should be seen as a statistical representation of money growth rather than as a description of actual Fed behavior. Leeper and Gordon (1991)
show that the results do not change when current values of
income and prices are permitted to predict money growth.
20. These VARs are estimated with the same lag lengths as in
the VARs with exogenous money growth.
21. A third variant on the traditional specification in equations
(3) and (4) is to impose that only current and past money
growth rates influence the interest rate but to allow other
variables to predict money. Leeper and Gordon (1992) consider this s p e c i f i c a t i o n and f i n d that a l l o w i n g m o n e y
growth to respond to other variables is sufficient to overturn
the traditional results portrayed in Chart 4.

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Rates." Review of Economics and Statistics 48 (August 1966):
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. The Channels of Monetary Effects on Interest
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, and Arthur Gandolfi. "The Lag in Monetary Policy as
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Christiano, Lawrence J. "Modeling the Liquidity Effect of a
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, and Martin Eichenbaum. "Liquidity Effects, Monetary
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. "Identification and the Liquidity Effect of a Monetary
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(January 1989): 75-83.
Cook, Timothy, and Thomas Hahn. "The Effects of Changes in
the Federal Funds Rate Target on Market Interest Rates in

Federal Reserve B a n k of Atlanta



the 1970s." Journal of Monetary Economics 24 (December
1989): 331-51.
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Espinosa, Marco. "Are All Monetary Policy Instruments Created Equal?" Federal Reserve Bank of Atlanta Economic Review 76 (September/October 1991): 14-20.
Friedman, Milton. "The Role of Monetary Policy." American
Economic Review 58 (March 1968): 1-17.
, and David Meiselman. "The Relative Stability of Monetary Velocity and the Investment Multiplier in the United
States, 1897-1958." In Stabilization Policies, Commission
on Money and Credit, 165-268. E n g l e w o o d Cliffs, N.J.:
Prentice-Hall, Inc., 1963.
Friedman, Milton, and Anna J. Schwartz. A Monetary
History
of the United States, 1867-1960. Princeton, N.J.: Princeton
University Press, 1963a.
. "Money and Business Cycles." Review of Economics
and Statistics 45 (February 1963b, Supplement): 32-64.
Fuerst, Timothy S. "Liquidity, Loanable Funds, and Real Activity." Journal of Monetary Economics 29 (February 1992):
3-24.
Gali, Jordi. " H o w Well Does the IS-LM Model Fit Postwar
U.S. Data?" Columbia University. Photocopy, August 1990.
Gibson, William E. "The Lag in the Effect of Monetary Policy
on Income and Interest Rates." Quarterly Journal of Economics 84 (May 1970a): 288-300.
. "Interest Rates and Monetary Policy." Journal of Political Economy 78 (May/June 1970b): 431-55.

Economic Reuieiv

15

Goodfriend, Marvin. "Interest Rates and the Conduct of Monetary P o l i c y . " Carnegie-Rochester
Conference
Series on
Public Policy 34 (Spring 1991): 7-30.
Heller, H. Robert. "Implementing Monetary Policy." Federal
Reserve Bulletin 74 (July 1988): 419-29.
King, Robert G. "Money and Business Cycles." University of
Rochester. Photocopy, July 1991.
Laidler, David E.W. The Demand for Money. 3d ed. New York:
Harper and Row, 1985.
Leeper, Eric M., and David B. Gordon. "In Search of the Liquidity Effect." Board of Governors of the Federal Reserve
System, International Finance Discussion Paper No. 403,
July 1991.
• "In Search of the Liquidity Effect." Journal of Monetary Economics 29 (forthcoming, June 1992).
Litterman, Robert B., and Laurence Weiss. "Money, Real Interest Rates, and Output: A Reinterpretation of Postwar U.S.
Data." Econometrica 53 (January 1985): 129-56.
Lucas, Robert E., Jr. "Liquidity and Interest Rates." Journal of
Economic Theory 50 (April 1990): 237-64.
Melvin, Michael. "The Vanishing Liquidity Effect of Money on
Interest: Analysis and Implications for Policy." Economic
Inquiry 21 (April 1983): 188-202.
Mishkin, Frederic S. A Rational Expectations
Approach
to
Macroeconometrics.
Chicago: University of Chicago Press,
1983.
Reichenstein, William. "The Impact of Money on Short-Term
Interest Rates." Economic Inquiry 25 (January 1987): 67-82.
Roberds, William. "What Hath the Fed Wrought? Interest Rate
Smoothing in Theory and Practice." Federal Reserve Bank
of Atlanta Economic Review 77 (January/February 1992):
12-24.

16

Economic Review




Sargent, Thomas J. "A Classical Macroeconometric Model for
the United States ."Journal of Political Economy 84 (1976):
207-37.
Sims, Christopher A. "Comparison of Interwar and Postwar
Business Cycles: M o n e t a r i s m R e c o n s i d e r e d . " American
Economic Review Papers and Proceedings 70 (May 1980):
250-57.
• "Are Forecasting Models Usable for Policy Analysis?"
Federal Reserve Bank of Minneapolis Quarterly Review 10
(Winter 1986): 2-16.
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1987.
• "Identifying Policy Effects." In Empirical
Macroeconomics for Interdependent Economies, edited by Ralph C.
Bryant et al., 305-21. Washington, D.C.: The Brookings Institution, 1988.
Stokes, Houston H., and Hugh Neuburger. "The Effect of Monetary Changes on Interest Rates: A Box-Jenkins Approach."
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534-48.
Strongin, Steven. "The Identification of Monetary Policy Disturbances: Explaining the Liquidity Puzzle." Federal Reserve Bank of Chicago. Photocopy, December 1991.
Tarhan, Vefa. "Does the Federal Reserve Affect Asset Prices?"
Loyola University of Chicago. Photocopy, June 1991.
Tobin, James. "Liquidity Preference and Monetary Policy." Review of Economics and Statistics 29 (May 1947): 124-31.
• " M o n e y and Income: Post Hoc Ergo Propter H o c ? "
Quarterly Journal of Economics 84 (May 1970): 301-29.

.May/June 1992

i n c h a n g é Rate
Variability and
International Trade

Vikram Kumar and Joseph A. Whitt, Jr.

M
m

uring the past two decades, the growth rate of international
trade among the major industrial countries has been substant
tially slower than during the 1950s and 1960s. Moreover, exK
change rate variability has been much greater since the 1973
breakdown of the Bretton Woods system of fixed exchange
rates. Are the two phenomena connected?

Kumar is an assistant
professor in the Department
of Econom ics at Davidson
College and a former visiting
scholar at the Atlanta Fed.
Whitt is an economist at the
Atlanta Fed currently visiting
the Board of Governors.


Federal
Reserve B a n k of Atlanta


•
M
W

To investigate the question of a relationship, this article examines the
record of exchange rate variability for a number of major industrial countries over the past several decades. The increase in variability since the
Bretton Woods system collapsed has not been uniform, particularly as
members of the European Monetary System (EMS) have had some success
in limiting the variability of their effective exchange rates. The study explores possible explanations for the variability, focusing on whether the
move to flexible exchange rates may have added variability and uncertainty
to monetary and fiscal policy, both of which have a major impact on marketdetermined exchange rates. In addition, the authors consider the effect of
exchange rate variability on the volume of international trade. Though some
investigators are unable to find evidence of any influence, an accumulating
body of research points toward a modest depressing effect. The possibility
of a depressing effect is serious because decreases in international trade
would reduce the extent of economic specialization, which promotes economic welfare in all countries.

Economic Reuieiv

17

.Exchange Rate Systems since
World War n
The Bretton Woods system was created in the waning days of World War II by negotiation among governments, particularly the United States and Great
Britain. It was a comprehensive attempt to create a
system of fixed exchange rates, modeled in many respects after the gold standard of the late nineteenth
century. However, contrary to the gold standard, the
Bretton Woods agreement provided for occasional
changes in exchange rates if a country were in "fundamental disequilibrium." In particular, if a country experienced a continuing balance-of-payments deficit
that reduced its international reserves to unacceptable
levels, it could devalue its currency in order to reverse
the deficit.
For a number of years the Bretton Woods system
appeared to perform well. The volume of international trade a m o n g the m a j o r industrialized countries
grew rapidly, as did real (inflation-adjusted) incomes
in those countries. E x c h a n g e controls on trade in
goods and services were reduced or eliminated without
putting u n d u e pressure on g o v e r n m e n t - c h o s e n exchange rate pegs.
By the mid-1960s, however, the system was being
strained. The British pound suffered as a widening
trade deficit plus capital outflows caused a reduction
in official reserves. For several years the British government attempted to maintain the pound's exchange
rate through a variety of special tariffs and limitations
on imports, plus special subsidies for exports. These
measures not only reduced the efficiency of the British
economy but ultimately failed to stave off a substantial
devaluation of the pound, which occurred in late 1967.
Advocates of flexible exchange rates suggested that, if
their preferred system had been in place, the special
tariffs and subsidies would never have been imposed,
and the pound would have depreciated gradually instead of all at once, with less consequent disruption of
the economy.
F u r t h e r strains a r o s e that i n v o l v e d the U n i t e d
States, Germany, and Japan. Each of these countries
felt that its policy choices were being restricted in an
unacceptable manner by the continuation of the Bretton Woods system. 1 In early 1973 these pressures resulted in the end of the Bretton Woods system as
governments gave up trying to peg exchange rates.
Since then exchange rates between the major currencies have been floating, determined on a day-to-day
basis by market forces. Nevertheless, g o v e r n m e n t s

18
Economic Review



have continued to influence exchange rates significantly: changes in monetary or fiscal policy sometimes cause dramatic changes in exchange rates, and
governments have sometimes directly intervened in
exchange markets.
Moreover, not all exchange rates have been floating
freely. Many small countries have chosen to peg to
their major trading partners. In addition, a group of European countries have banded together in the European
Monetary System. Their currencies are essentially
pegged within narrow bands vis-a-vis members of the
group, but they float together as a bloc in relation to
outside countries, such as the United States and Japan.

E x c h a n g e Rate Fluctuations
Prior to the advent of floating exchange rates in
1973, debate on the effects of exchange rate variability
was largely theoretical because the prevailing system
imposed tight restrictions on e x c h a n g e rate movements. 2 Supporters of fixed exchange rates used concern about the possible trade-dampening effects of
exchange rate variability as one argument for maintaining the Bretton Woods system. 3 On the other side,
supporters of flexible exchange rates argued that allowing exchange rates to float would not result in wild
gyrations; instead, exchange rates would move only in
r e s p o n s e to c h a n g e s in d e m a n d or supply, w h i c h
would normally develop slowly. Sharp m o v e m e n t s
would p r e s u m a b l y occur only occasionally, in response to major events such as unexpected reversals
of g o v e r n m e n t policy (Milton Friedman 1967, 77;
Harry G. Johnson 1972, 213). They pointed to the experience of Canada, whose flexible exchange rate did
not fluctuate wildly from 1950 to 1962. 4 They argued
further that market participants who wished to avoid
bearing exchange rate risk would be able to do so by
hedging in forward and futures markets.
After the collapse of the Bretton Woods system and
the move to generalized floating among the major exchange rates, it soon became clear that large movem e n t s in e x c h a n g e rates w e r e o c c u r r i n g f a r m o r e
frequently than many flexible rate advocates had expected. The increase in the volatility of the nominal
exchange rates between the leading currencies after
Bretton Woods is seen in Chart 1. For instance, Egon
Sohmen (1969, 228) reports that from 1952 to 1960
the floating Canadian dollar never moved more than 6
percent against the U.S. dollar in a single year; the average range of fluctuations was 3.85 percent in a year.

.May/June 1992

Chart 1
Nominal U.S. Dollar Exchange Rates, 1 9 6 0 - 9 0
(Annual average)
Deutsche Mark

French Franc

2

British Pound

-

0.5 -

1
0 I i i i I i i i l i i i I i i I I i i i I I i i l i I i l i I iI
1959

1963

1967

1971

1975

1979

1983

1987

1991

0 I

I i

1959

II

4- •

1963

:

I I -I I

1967

r I

1971

I

I I

!

1975

Il

I

4- H

1979

I I I

1983

I

I

14 !

1987

H

1991

S o u r c e : C a l c u l a t e d by the Federal Reserve B a n k of Atlanta using International M o n e t a r y Fund International Financial Statistics.

By contrast, Joseph A. Whitt, Jr. (1990, 9-11) reports
that during the period from June 1973 to December
1989, the British pound/U.S. dollar rate had fourteen
separate episodes during which it moved more than 10
percent in six months. Moreover, frequent large fluctuations were not confined to the British pound; the German mark and the Japanese yen had similar numbers
of large fluctuations vis-a-vis the U.S. dollar.


Federal
Reserve B a n k of Atlanta


Real trade flows presumably are affected by real
exchange rates—that is, nominal rates adjusted for
domestic and foreign inflation. Moreover, different
bilateral exchange rates commonly move by different
amounts, making it useful to have a single summary
measure such as the effective exchange rate. The effective exchange rate is a weighted average of a country's bilateral exchange rates. The weights are based

Economic Reuieiv

19

on trade shares, ensuring that a major trading partner
gets more weight than a minor one. A variety of statistical measures of exchange rate volatility have been
used in the literature, though as Peter B. Kenen and
Dani Rodrik (1984, 6) argue, they all tend to yield
similar results over longer periods. 5 Chart 2 presents
perhaps the most common statistic—the standard deviation of percentage changes in the exchange rate,
calculated using the real effective exchange rate.
In Chart 2 volatility of the real effective U.S. dollar,
the Japanese yen, and the British pound is depicted in
the top panel, and of the Dutch guilder, the German
mark, and the French franc in the bottom panel. It is
evident that with the sporadic exceptions of the guilder
and the pound, instability in the leading currencies was
small and uniform during much of the fixed rate period. The crisis in the Bretton Woods system at the end
of the 1960s was accompanied by sharp increases in
the volatility of European effective real rates. The effects of revaluations of the guilder in 1961 and 1962,
the 1967 devaluation of the pound, and the 1969 revaluation of the mark and devaluation of the franc are evident in the charts. In the transition years between
regimes, from 1971 to 1974, exchange rate volatility
was pronounced and increasing, but it was expected to
abate as exchange markets found their equilibria. 6 Although some currencies did begin to settle down, the
volatility continued to be significant. Only in the late
1970s did the volatility begin to subside for some currencies, but there was generally a pronounced increase
in volatility during the flexible rate regime.
Table 1 provides the mean (average) volatility and
the standard deviation of volatility in real effective exchange rates for a major part of the Bretton Woods period (1961-71) and the floating rate period (1975-88),
as well as for the European Monetary System years
starting in 1979, for currencies of eight countries. It is
evident in the top panel of Table 1 that the average
volatility in the real effective exchange rate was larger
during the floating rate period for all currencies except
the guilder. In m a n y instances mean volatility increased to a level 200 percent to 300 percent of its
Bretton Woods level. In most cases the currencies
maintained their relative volatility rankings (given in
parentheses) between regimes; the yen and the British
pound were consistently high in volatility, and the
Canadian dollar consistently low. The U.S. dollar is
something of an exception; it had the lowest volatility
in this group under Bretton Woods but had the thirdhighest volatility during the float.
The subperiod from 1979 to 1988 is especially revealing; these are the years in the sample during which

20

Economic Review




the European Monetary System formally existed. It is
the stated aim of the European Monetary System to
contain currency fluctuations between members within
smaller bands than the free market has generated; accomplishing that goal calls for strict policy coordination and maintaining comparable inflation rates across
member nations. It would be fair to say that an implicit
objective of the EMS is to stabilize real exchange rates
between members. The results in Table 1 point to the
stunning success of the system in this regard. The
mean volatility of the currencies of the four original
EMS members in the table—France, Germany, Italy,
and the Netherlands—declined in this period. As the
bottom panel of Chart 2 shows, by the end of the period the volatility measures for three of these countries
had reached rough convergence at the lowest levels
since the a d v e n t of f l o a t i n g ; in s o m e cases these
volatility levels were comparable to those in the 1960s.
The bottom panel of Table 1 gives the standard deviation of the volatility measures. It provides a measure of the c h a n g e in volatility f r o m year to year
during a given sample period. Between the fixed and
the floating exchange rate periods, no systematic pattern emerges regarding the dispersion of real effective
rate volatility. Both low and high volatility currencies
experienced increases and decreases in the variability
of volatility. Within the floating rate period, however,
the variability has either declined or remained constant
for all the sample currencies since formation of the
European Monetary System.
Apart from the central tendencies observed above,
the year-to-year relationships between currencies are
v a g u e and s h i f t i n g . T h e c o r r e l a t i o n s b e t w e e n the
volatility measures of the various currencies are given
in Table 2. The correlations for the full floating rate period are given below the diagonal; above it are the
numbers for the EMS years. Over the full floating sample period U.S. dollar volatility has been related negatively to the Canadian dollar but positively to the yen.
The deutsche mark and the franc have both been related positively to the guilder, negatively to the pound,
and positively with each other. The lira's volatility
moves against the yen's but with the guilder's. In the
1979-88 subsample, the volatility in the deutsche mark
and the guilder continues to be positively associated,
and there is a strong tripartite relationship between
fluctuations in the lira and the U.S. and Canadian dollars. Somewhat surprisingly, all the other intra-EMS
correlations fade away; no wider systematic relationships are evident. Taken as a whole then, exchange rate
volatility seems to elude simple patterns of associations,
and those that do exist seem to be less than permanent.

May/June 1992

Chart 2
Exchange Rate Volatility, 1 9 6 1 - 8 8
(Real effective rates)
Standard Deviation

3.5

_

3.0

"

1

\
1

Y

/

1

/

/'

\

'

r%

V

'

\

v

/

\

/

Sl

i

i

^

0.5

/

\

x
\

v // / K \
w
\

// ' // V\ / ' /

1.0

I'

.7

/, — V\

M
1

/

\

;i

\

//X

\

'N

:

1

/'/

/

\

/

/ \

1.5

^

/

/ \

2.0

\

/

A

1
\
1

2.5 - -

japan — J

/ United Kingdom

\

\

v

/

U n i t e d States

—<—i—i—i—i—i—I—i—i—i—i—1—l—l—1—I—1—I—

1966

1961

1986

1981

1976

1971

3.5

3.0 France

2 . 5 -Germany
2 . 0 -•

1966

1961
Note: Volatility

for a given

year was measured

used in the calculations.

For example,

by the standard

deviation

the weight of France

of eleven

during the base year,

monthly

in the U.S. effective

(exports plus imports) as a fraction of total U.S. trade with the included

1986

1981

1976

1971

countries

percentage

exchange

changes.

rate equals

(data on twenty

Total trade weights

total U.S. trade with

industrial

countries

were

were
France

included)

/ 977.

Source: Calculated by the Federal Reserve Bank of Atlanta using International Monetary Fund International Financial Statistics.

Federal
Reserve Bank of Atlanta



Economic Reuieiv

21

Table 1
Mean and Standard Deviation of Real Effective Exchange Rate
Volatility Measures for Selected Countries

1961-71

1975-88

1979-88

Mean Volatility
Canada (7, 7)

0.55

1.05

1.06

United States (8, 3)

0.39

1.43

1.57

Japan (4, 1)

0.88

2.57

2.88

France (3, 5)

0.93

1.17

1.08

Germany (5, 6)

0.85

1.16

0.97

Italy (6, 4)

0.57

1.40

1.13

Netherlands (1, 8)

1.07

0.86

0.76

United Kingdom (1, 2)

1.07

2.03

2.17

Standard Deviation of Volatility
Canada (>1, <->)

0.32

0.24

0.24

United States (T, I )

0.11

0.41

0.34

Japan (T, i )

0.09

0.76

0.55

France (1, <->)

0.86

0.35

0.35

Germany (J-, -I)

0.63

0.44

0.19

Italy (T, I )

0.10

0.56

0.17

Netherlands (4,1)

0.43

0.25

0.17

United Kingdom ( i , -i)

1.05

0.41

0.34

N o t e : Exchange
effective

rate volatility
exchange

ing of the country

for a given

year was measured

rate in that year. All numbers
in ascending

for the 1975-88 period.

order of volatility

The arrows in parentheses

by the standard

have been scaled
of its currency.
indicate

deviation

of the eleven

monthly

up by a factor of 100. The numbers
The first number

the direction

of change

percentage

is for 1961-71; the second
between

adjacent

changes

in parentheses
number

in the real

denote

the rank-

denotes

the rank

columns.

Source: C a l c u l a t e d by the Federal Reserve Bank of Atlanta using International M o n e t a r y Fund International Financial Statistics.

22

Economic Review




. M a y / J u n e 1992

a
rt)

Table 2
Correlations between Exchange Rate Volatility Measures
For Selected Countries, 1975-88 and 1979-88

Canada

>

Canada

United States

Japan

France

Germany

Italy

-0.551*

0.431

0.573*

0.389

-0.639**

0.143

-0.482*

United States

0.542

0.103

0.053

0.300

0.407

0.488

-0.235

0.516

-0.329

0.915***

-0.468

0.219

France

0.119

-0.116

0.012

-0.267

-0.130

-0.195

0.669*

-0.005

-0.429

-0.615**

0.169

0.439

Netherlands

0.149

-0.297

-0.248

0.554**

0.781***

United Kingdom

0.209

0.337

0.376

Italy

Note: Correlations
0.10,

for the 1975-88 period are below

the diagonal;

-0.460*

-0.296

-0.236

0.071

-0.513*

those for the 1979-88 period are above the diagonal.

The symbols

Source: Calculated by the Federal Reserve Bank of Atlanta using International Monetary Fund International Financial Statistics.

to




0.536

-0.234

0.680***

respectively.

Il OJ

-0.1.

0.073

-0.038

0.107

Germany

0.427

United Kingdom

0.871***

-0.162

Japan

0.618*

Netherlands

-0.149

***, **, * denote significance

levels of 0.01, 0.05, and

Sources of Exchange Rate Fluctuations
What causes the large exchange rate fluctuations
described a b o v e ? T h e m o s t c o m m o n explanations
economists offer have focused on the role of expectations about the future in determining today's exchange
rates.
To introduce the role of expectations, it is instructive to consider the open interest parity condition,
which essentially states that if capital mobility is not
restricted, investors will engage in arbitrage between
financial markets to ensure equalized expected rates
of return on domestic and foreign securities. In this
context, capital mobility means that at least some investors can readily borrow or lend in both the domestic and foreign financial markets without government
restrictions.
The open interest parity condition can be represented mathematically as follows:
l + r , = ( l + r;){[£/S, + 1 )]/S,}.

(1)

In equation (1) r and r are the interest rates on domestic and foreign bonds, respectively. S[ is the domestic currency price at time t of a unit of foreign
currency, and Et (S/+l) is the expectation prevailing at
time t regarding the exchange rate one period hence.
The left side of the equation represents the expected
return to a U.S. investor on a U.S. bond, while the
right-hand side represents the expected return to a
U.S. investor on a foreign bond investment, taking into account conversion between dollars and the foreign
currency. Profit-seeking investors presumably compare the two returns and invest in the one promising
h i g h e r r e t u r n s ; if m a n y investors m a k e the s a m e
choice, domestic and foreign expected returns are
forced into equality.
Suppose, for example, that a U.S. investor wishes
to decide between buying a $100.00 U.S. government
bond and an equivalent amount of French bonds at the
prevailing exchange rate of St = $0.20/franc. If the
U.S. and French interest rates are 8 percent and 5 percent, respectively, the investor will receive $108.00
from the U.S. bond one year later. An alternative strategy would be to convert $100.00 into ($100/5,) = 500
francs. At the 5 percent French interest rate the investor would receive 500(1 + 0.05) = 525 francs one
year later. If the U.S. investor is interested in dollardenominated returns, he or she will be indifferent to
the choices if and only if the proceeds of the French
bond (525 francs) are expected to be worth $108.00—

24
Economic Review



that is, £,(S, +1 ) = $108/525 = $0.2057/franc. Hence the
investor will be in equilibrium only if the dollar is expected to depreciate by roughly 3 percent. In other
words, the expected change in the exchange rate offsets the interest rate differential, leaving the investor
indifferent. 7
It is clear that for given interest rates r and r*, equation (1) can be solved for the ratio Et(St+l)/St but not
for Sf alone. For example, if r is equal to r\ equation
(1) implies that Sf must equal Et(St+l), but it provides
no way of determining whether St is $0.20 per franc,
$0.13 per franc, or any other amount, as long as it
equals Et(St+]). Indeed, an infinite number of values
of St are consistent with open interest parity and the
given values of r and r . Moreover, the expectation
Et(S/+ j) is never directly observed even though data
for S t are available whenever the exchange market is
open.
If governments are not pegging exchange rates but
are allowing market forces to determine rates, which
of the infinite number of possible values of St will
prevail? A partial answer is provided by equation (1):
given interest rates r t and rf*, plus the expected future
exchange rate Et(St+i), only one value of today's exchange rate is consistent with open interest parity.
Furthermore, Ronald I. McKinnon (1988), among
others, argues that expectations about exchange rates
are volatile, being extremely sensitive to minor changes
in expectations about economic fundamentals such as
monetary and fiscal policy. If so, equation (1) implies
that the spot exchange rate will be volatile as well except in the unlikely event that changes in expectations
are exactly offset by the correct pattern of interest rate
movements. Any event—the fall of the Berlin Wall, an
announcement like the annual release of the President's budget proposals, or even a change in the attitudes of market participants—that changes market
expectations about the future value of the exchange
rate will feed back immediately into changes in the
current exchange rate Sr
The above discussion shows how today's exchange
rate should be affected heavily by the expected future
exchange rate, but it begs the question of what determines the expected future exchange rate. To answer
that question various economists have developed the
idea that exchange rates are asset prices, somewhat
analogous to stock prices.
In the case of stocks the fundamental determinant
of value is earnings; the theory of finance indicates
that the price of a stock today is equal to the present
value of expected future earnings. For exchange rates
the f u n d a m e n t a l d e t e r m i n a n t s presumably include

.May/June 1992

monetary policy, fiscal policy, real growth, and a variety of other factors. Accordingly, it seems reasonable
to think that the expected future exchange rate would
be determined by expected monetary policy, fiscal
policy, and other conditions.

than a 10 percent j u m p expected to occur ten weeks
f r o m now. Finally, an increase in variability of the
money stock will raise exchange rate variability. Accordingly, unstable monetary policy is one possible
source of exchange rate fluctuations.

Michael Mussa (1976) formalized this result (see
the box on page 26). Within the basic framework of an
o p e n - e c o n o m y m o n e y - d e m a n d m o d e l , he d e m o n strates three important features of exchange rate determination. First, a c o u n t r y ' s current e x c h a n g e rate
depends on current monetary policy and economic
conditions and on expectations about the entire future
path of these factors. Thus a change in expectations as
well as a change in current conditions will immediately influence the current exchange rate. Second, the impact of a change in expectations in the distant future is
less than the impact of the same change expected to
occur soon. For example, a 10 percent j u m p in the
money supply expected to occur ten years from now
will have much less effect on today's exchange rate

According to Paul De G r a u w e ' s (1989) "reduced
discipline" hypothesis, the shift from fixed exchange
rates to the current system of flexible exchange rates
gave governments increased leeway in policy choices
in both m o n e t a r y and fiscal policy. In the M u s s a
framework increased variability of the money stock
directly increases exchange rate variability. Although
a measure of fiscal policy does not appear explicitly in
Mussa's analysis, changes in fiscal policy have an influence through their effect on interest rates; moreover,
in many countries budget shortfalls are frequently financed by monetary expansion.
What evidence is available regarding the variability in economic policy? The upper panel of Table 3
p r e s e n t s the m e a n and s t a n d a r d d e v i a t i o n s of the

Table 3
Mean and Standard Deviation in Budget Deficit/GDP and
In the Growth of Money Supply during the Fixed and Flexible Exchange Rate Regimes

Fixed Rates
Mean

Flexible Rates

Standard Deviation

Mean

Standard Deviation

Budget Deficit/GDP
United States

-0.31

0.33

3.12

1.65

0.90

0.27

3.62

1.26

Germany

-0.08

0.35

-1.50

0.63

France

-0.18

0.15

-1.60

1.16

Japan

Growth in M1
United States
Japan
Germany
France
N o t e : The fixed rate period
1960 to 1971. Data
1974-89 period.

4.21

2.08

7.01

3.58

20.48

8.37

6.70

4.53

8.47

3.34

8.77

6.46

10.11

5.40

10.35

6.33

figures for the United
for the flexible

States and France

rate period

The budget deficit is the actual,

are from

are based on data from

1974 to 1990 except

not full-employment

or structural,

1959 to 1971; for Japan

for Germany's

budget deficit

and Germany,

data,

which

cover

from
the

deficit.

S o u r c e : C a l c u l a t e d by the Federal Reserve Bank of Atlanta using International M o n e t a r y Fund International Financial Statistics.

Federal Reserve B a n k of Atlanta



Economic Reuieiv

25

Exchange Rates and Expected Change in Policy and Economic Conditions

M u s s a (1976) provides a simple illustration of the influence of expectations about policy and e c o n o m i c conditions on the e x c h a n g e rate. S u p p o s e that m o n e y market
equilibrium for the h o m e country in period t is represented by the following (all variables are in logarithms):

It is p r e s u m e d that m a r k e t p a r t i c i p a n t s k n o w t h a t
w h e n they reach period t + 1, its prevailing exchange rate
will be determined in the s a m e way as in period t. Only
the time subscripts will be different:
st+l = ll/(a

mt = mf = asr - ¡3D, + J J

(B1)

w h e r e m t is t h e n o m i n a l stock of m o n e y in t h e h o m e
country, mf is nominal m o n e y d e m a n d , st is the e x c h a n g e
rate (domestic currency per unit of foreign currency), £>f
is the expected rate of depreciation of the h o m e currency,
and Zt measures the effect on m o n e y d e m a n d of all other
variables, such as real output.
Although equation ( B l ) m a y appear unusual, it is actually s i m i l a r to m o r e f a m i l i a r f o r m u l a t i o n s of m o n e y
market equilibrium, in which nominal m o n e y is positively related to the price level, negatively related to the interest rate (or sometimes the inflation rate), and positively
related to output. In equation ( B l ) , the term ast takes the
place of the price level; other things being equal, a rise
(depreciation) of the e x c h a n g e rate raises the h o m e c o u n t r y ' s price level, thereby raising the nominal d e m a n d for
money. H e n c e a should be positive.
Similarly, the term ~f3Di takes the place of the m o r e
familiar interest (or inflation) rate. Indeed, Dl is closely
related to the d o m e s t i c interest rate t h r o u g h the o p e n interest parity condition. The expected depreciation rate
is defined as follows:
D, = E,[ln(Sl+l)

- ln(S)] = Er(sl+l)

- sr

(B2)

U s i n g the a p p r o x i m a t i o n that f o r small values of x,
ln( 1 + x) = x, and taking logarithms of both sides of equation (1) yields the following transformation of equation (1):

=

+

~ -V

(B3)

Hence
D=r,

-/•;.

(B4)

T a k i n g foreign interest rates as given by conditions
abroad, equation (B4) s h o w s that increases in expected
depreciation, Dt, are likely associated with increases in r ,
the d o m e s t i c interest rate. In the usual m o n e y - d e m a n d
e q u a t i o n , increases in interest rates r e d u c e m o n e y demand. H e n c e it is expected that -¡3, the coefficient on D (
in equation (B1), should b e negative.
Substituting equation (B2) into ( B l ) and rearranging
gives the solution for t o d a y ' s exchange rate in terms of
the m o n e y s u p p l y and Zf t o d a y , plus t h e e x p e c t e d exc h a n g e rate:
5, = [1 /(a + mm,

26

Economic Review




- Z, +

fiEt{sM)l

+

mmt+l

— Zl+i + (3E[+l(st+2)].

(B6)

T o d a y ' s expectation about next period's exchange rate can
b e obtained by calculating the expected value of equation
(B6).
E,{s^ = [\l{a+mEt{mt+i)

(B7)

-£i(Z;+|)+/3£i[£(+|(.,+2)](
= [l/(a +(3)][El(ml+l

— Z[+l) + /3Er(si+2)].

Substituting equation (B7) back into (B5) yields an expression for
in terms of current and expected m o n e y
and other variables (Z), plus the expected exchange rate
two periods hence, E,(sr+2). Repeating this procedure over
and over for exchange rates farther in the future (Et[sf+,l
and so on) results in an expression for today's exc h a n g e rate that involves only the e c o n o m i c f u n d a m e n tals, current and expected m o n e y supplies and Zs.
st=[l/(a

+ j3)]{(mt

- Z )

+ W/(c* + P)\2[E,(ml+2-Zi+2)]

(B8)

+

...}.

E q u a t i o n ( B 8 ) clearly s h o w s that t o d a y ' s e x c h a n g e
rate depends not only on t o d a y ' s values of m, and Z/ but
also on the entire expected future path of these variables.
For example, any alteration in the expected future course
of monetary policy will have an immediate impact on the
e x c h a n g e rate today.
A n o t h e r feature of equation ( B 8 ) that seems reasonable is that c h a n g e s in expectations about the distant future h a v e less i m p a c t than c h a n g e s e x p e c t e d to o c c u r
soon. T h e reason for this result is that the terms involving expectations in equation (B8) are multiplied by p o w ers of [f3/(a + ¡3)].
A s discussed earlier, a and [3 should both be positive;
hence \J3/(a + /3)| should be positive but less than one.
T h e expectation about the m o n e y supply and other variables n periods h e n c e , £ ; ( m ; + ) | - Zt+n), is multiplied by
[(3/(a + (3) \ raised to the nth power; for periods farther in
the future, n is larger, but the c o e f f i c i e n t [(3/(a + (3)]"
shrinks toward zero. A n o t h e r result that s e e m s intuitively clear f r o m inspection of equation (B8) is that an increase in the variability of the m o n e y stock, other things
b e i n g equal, will raise t h e variability of the e x c h a n g e
rate.

(B5)

.May/June 1992

share of the budget deficit as a proportion of gross domestic product (GDP) for four countries. In each case
the variability during the flexible rate regime has increased significantly; in three of the countries the
standard deviations have more than quadrupled. The
lower panel provides the means and standard deviations of the growth in M1 for the same countries. It is
apparent that except for Japan the growth in money
supply has fluctuated more during the flexible rate period as well. These variations may partially explain
the volatility in exchange rates.
A study by De Grauwe (1989) raises the possibility
that the volatility in policy may not have been caused
by the "reduced discipline" required of governments
but rather that the large oil shocks of the 1970s may
have prompted large policy responses in their wake.
The question essentially seems to be whether fiscal
policy in particular is "truly" driven by external forces,
or, within the context of the particular political realities of modern democracies, it responds endogenously
to the given state of the economy. The fiscal policies
of the United States, Germany, and Japan, De Grauwe
notes, have diverged significantly since the late 1970s;
despite a common oil shock, countries have felt free to
chart independent courses of action, providing circumstantial support in favor of the "reduced discipline"
hypothesis.
It seems reasonable to believe that the behavior of
economic policy has had repercussions in currency
markets and made market exchange rates more variable. Concurrently, uncertainty regarding the future
course of policy may have cast a long shadow on the
market's ability to predict exchange rates with any
reasonable degree of accuracy. Here lies the core of
concern regarding exchange rate volatility. Expected
variations would rationally be incorporated into current decisions and may not impose any real costs. The
same is not true for unexpected changes. There is
considerable evidence that forward markets, where
traders hedge against exchange rate uncertainty, have
repeatedly failed to predict exchange rates by wide
margins and have often failed to predict correctly
even the direction of exchange rate changes (see, for
instance, Robert E. C u m b y and M a u r i c e O b s t f e l d
1984).
Has the exchange rate volatility observed since the
end of Bretton Woods been excessive in some sense?
The question is difficult to answer because economists
do not agree on what the appropriate amount of volatility is. One approach is based on purchasing-power
parity, which provides a simple, easy-to-calculate way
of estimating equilibrium exchange rates. According

Federal
Reserve Bank of Atlanta



to this approach, if the domestic rate of inflation exceeds the foreign rate of inflation by x percent over
some period, the domestic currency should depreciate
by that same x percent. Therefore, the volatility of the
exchange rate between two countries should be approximately the same as the volatility of price index
ratios.
In the upper panel of Chart 3 the percentage change
in the deutsche mark/dollar rate is plotted together
with the difference between German and U.S wholesale price inflation. 8 A positive change in the exchange
rate denotes an appreciation of the dollar. The lower
panel depicts the same for Japan. If purchasing-power
parity held exactly, the exchange rate line would coincide with the relative inflation line in each panel.
However, both panels show that while the directions
of change in the exchange rates have been as expected
for the most part, in the sense that they have moved to
offset inflation differentials, currency values have
m o v e d violently in c o m p a r i s o n with g o o d s prices
since the breakdown of Bretton Woods. 9 The "excessive" movement has not abated through time; rather, it
has increased. It appears that relative inflation differentials are able to explain only a small portion of the
change in exchange rates.
As an alternative to purchasing-power parity, it is
possible to use a more complex model that relates the
e x c h a n g e rate to a w i d e r v a r i e t y of f u n d a m e n t a l
determinants, such as money supplies, interest rates,
measures of fiscal policy, and the like. The analysis
in the box is a fairly simple example of this approach.
H o w e v e r , R i c h a r d A. M e e s e and K e n n e t h R o g o f f
(1983) and Meese (1990) have shown that fundamentals have not helped in the prediction of exchange
rates; naive random walk models that consider current exchange rates the best predictors of the future
yield consistently better forecasts than the structural
models.
The uncertain policy environment has been at least
partly responsible for exchange rate volatility. Jacob
A. Frenkel and Mussa (1980) question whether exchange rate volatility has been excessive, noting that
by various measures exchange rates have fluctuated
less than stock markets. They recommend that governments reduce the public's uncertainty about future
economic policy.
In any event, there is little evidence that exchange
rate volatility has shrunk since the early years of floating, except for those currencies constrained by the European Monetary System. Whatever its fundamental
source, the volatility seems likely to continue for the
foreseeable future.

Economic Reuieiv

27

Chart 3
Wholesale Price Inflation Differential and
Percentage Change in Nominal Exchange Rate, 1 9 6 0 - 9 0

Germany/United States

Japan/United States

S o u r c e : C a l c u l a t e d by the Federal Reserve Bank of Atlanta using International M o n e t a r y Fund International Financial Statistics.

28
Economic Review



M a y / J u n e 1992

i n t e r n a t i o n a l Trade and
Exchange Rate Volatility
Perhaps the most widely discussed concern about
exchange rate variability is its possible negative effect
on the volume of international trade and hence on economic welfare. In traditional international trade theory,
the basis for trade is comparative advantage: if the
United States is relatively efficient in producing machinery while France is relatively efficient in producing
champagne, both countries will benefit if the United
States exports machinery to France in exchange for
champagne.
Moreover, the joint welfare of the United States and
France would be maximized under conditions of free
trade. Tariffs or import quotas imposed by either country would reduce the volume of trade below the freetrade amount and would also reduce the joint welfare of
the countries below the free-market level. 10 (These conclusions were derived from economic theories that did
not explicitly include uncertainty about exchange rates.)
Exchange rate variability, or, more precisely, unexpected exchange rate movements, represent a source of
risk. For example, suppose that a U.S. firm is selling
machinery in France, with the sales contract specifying
that the U.S. firm is to receive payment of $100.00 per
machine three months after shipment is made. The
French importer placed the order because it had a contract to sell the machine in France for 525 francs. If,
when the contracts were signed, the exchange rate were
5 francs per dollar and the importer expected it to
remain so, then the importer would expect to pay its
debt to the U.S. firm with 500 francs, leaving a profit
for itself of 25 francs. However, if the exchange rate
changed in the weeks between the signing of the contracts and final settlement, the French importer's profit
would be affected. For instance, if the franc depreciated to 5.5 francs per dollar, the importer's expected
profit would turn into an actual loss of 25 f r a n c s ,
whereas if the franc appreciated to 4.75 francs per dollar the importer's profit would double to 50 francs." A
similar risk would be faced by companies involved in
exporting from France to the United States.
If firms are risk-averse, they would presumably
tend to favor low-risk activities and avoid high-risk
ones. Accordingly, if exchange risk increases, some
marginal firms would give up exporting or importing
entirely, and others would cut back their efforts in
these activities to concentrate on domestic sales, thereby causing the total volume of international trade to
decline. 12

Federal
Reserve Bank of Atlanta



Not surprisingly, the high variability of exchange
rates since 1973 has stimulated empirical work on the
relationship of exchange rate variability to the volume of
trade. Peter Hooper and Steven W. Kohlhagen (1978)
studied bilateral trade a m o n g m a j o r industrialized
countries during the period from 1965Q1 to 1975Q4;
they found no evidence that exchange risk significantly affected the volume of trade. Later work by the International Monetary Fund (1984), Padma Gotur
(1985), and Martin J. Bailey, George S. Tavlas, and
Michael Ulan (1986) reached similar conclusions.
Other authors have found evidence that exchange
rate variability does reduce trade volume. M. Akbar
Akhtar and R. Spence Hilton (1984) studied trade in
manufactures for the United States and West Germany.
For the post-Bretton Woods years from 1974 to 1981,
they found that increases in the standard deviation of
nominal effective exchange rates significantly reduced
Germany's total exports and imports and had a marginally significant negative impact on U.S. exports. N o significant impact on export or import prices was found
for either country. However, Gotur (1985) reported
that the results in Akhtar and Hilton are highly sensitive to small changes in specification or sample period; in addition, extending the analysis to include three
more countries yielded mixed results. In Gotur's view
the overall results did not, for the most part, support
the conclusion that exchange rate variability has had a
significant negative effect on the volume of international trade.
David O. Cushman (1983) studied U.S. and German bilateral trade flows with each other and with
several other industrialized countries, using a sample
period that began in 1965, during the Bretton Woods
era, and ended in 1975, two years after the definitive
move to floating exchange rates. Out of fourteen trade
quantity equations estimated, seven showed significant negative effects of exchange rate risk on trade
volume. However, in three cases a significant positive
effect was estimated.
In further analysis, Cushman (1986) considered the
possibility of third-country effects on risk. For example, if the riskiness of the pound-mark and mark-dollar
increased substantially, trade flows between the United
States and the United Kingdom might rise despite an
increase in bilateral risk as exporters in both the United
States and United Kingdom shifted their efforts away
from the even more risky German market. Using data
on U.S. exports Cushman found empirical evidence
that third-country effects are important. He concludes
that, as a result of exchange risk, U.S. exports to six
major countries were reduced only 0.5 percent in 1967,

Economic Reuieiv

29

when pegged exchange rates prevailed, but the negative effect grew to over 2 percent of exports in the early
part of the floating rate period (1974Q3 to 1975Q2)
and to 4.6 percent in 1983. Cushman (1988) studied
U.S. bilateral trade flows during the period of floating
exchange rates only. He concluded that, in the absence
of exchange rate risk, U.S. imports from the countries
included would have been about 9 percent higher and
U.S. exports about 3 percent higher, on average.
Kenen and Rodrik (1986) examined the effects of
various measures of real effective exchange rate volatility on manufactured imports of eleven m a j o r ind u s t r i a l i z e d c o u n t r i e s , using data solely f r o m the
post-Bretton Woods era. In four of the eleven cases
(the United States, Canada, West Germany, and the
United Kingdom) they found a statistically significant
negative impact of volatility on import volume. In
three cases there is a negative but insignificant impact,
and in the other four cases the sign is wrong (positive)
but insignificant.
Jerry G. Thursby and Marie C. Thursby (1987) studied bilateral exports among seventeen industrialized
countries. For ten of them, exchange rate variability
has a significant negative effect on exports; for the
others, this variable is insignificant. Unfortunately, because Thursby and Thursby have data only on nominal
exports and not on the volume of trade, it is uncertain
whether their significant results reflect the impact of
exchange rate variability on export volumes or on export prices.
In a study of long-run growth rates of bilateral trade
flows among ten major industrial countries, De Grauwe
(1988) analyzes two periods: a period of fixed exchange rates (1960-69) and a period of floating rates
(1973-84). A unique feature of De G r a u w e ' s work
is the inclusion of variables to represent trade integration. For example, he posits that during the 1960s, even
after accounting for the other variables such as income
growth or relative price shifts, French exports to Germany would be likely to grow faster than French exports to the United States because of the reductions in
trade barriers that occurred during those years as a
result of F r e n c h and G e r m a n m e m b e r s h i p in the
E u r o p e a n C o m m u n i t y (EC). This effect on export
growth rates would not be permanent; once the process of trade barrier reduction was completed and industries had time to adjust to the new pattern of trade
restrictions, this differential in growth rates would fade
away.
Besides a trade integration variable for the original
members of the EC, De Grauwe also includes a variable to pick up any effects on export growth f r o m

30

Economic Review




1973 to 1984 of the addition of the United Kingdom to
the European Community as well as variables to pick
up the extraordinary growth of Japanese exports as
that country was integrated into world markets.
De Grauwe found that exchange rate variability, especially variability of the real exchange rate, has a significant negative impact on the growth rate of trade
volumes. The trade integration variables were also important determinants of trade flows; other things being
equal, trade between the United K i n g d o m and the
original members of the EC grew an extra 5 percent
per year in the years following U.K. entry.
Overall, the average rate of growth of international
trade among these ten countries from 1973 to 1984 was
less than half the rate prevailing in the earlier period
(1960-69). According to De Grauwe's results, about
half the decline can be attributed to the slowdown in
real income growth that occurred in most industrial
countries after 1973. About 30 percent of the decline
resulted from a slowdown in trade integration—a slowing in Japan's trade penetration into other markets and
in trade integration among the original members of the
EC, only partly offset by the reduction in trade barriers
between the United Kingdom and the original members of the EC. The increase in exchange rate variability after the breakup of Bretton Woods accounts for the
remaining 20 percent of the overall decline.
T h e importance of e x c h a n g e rate variability in
explaining the decline in trade growth between the
two periods is not uniform for all the countries in De
Grauwe's study. For intra-European Community trade
(bilateral trade among the original members of the European Community), the declining rate of trade integration accounts for most (two-thirds) of the trade growth
slowdown; exchange rate variability accounts for only
about 5 percent of the decline. Of course, the original
European Community members had less variability of
within-group exchange rates than the other countries,
perhaps reflecting the impact of the European Monetary System. By contrast, for trade that was not between two original European Community members, De
Grauwe found that about one-third of the decline in
trade growth from the earlier period to the later one results from the increase in exchange rate variability.

Conclusion
Accumulating evidence supports the view that exchange rate fluctuations tend to reduce international
trade, thereby harming economic welfare. However,

.May/June 1992

the evidence is not unanimous, and the negative effect
on trade does not appear large enough to make reducing e x c h a n g e rate variability a top priority of the
world community. The successful operations of the
European Monetary System demonstrate that it is still
possible to limit exchange rate fluctuations, but it is
doubtful whether a similar system will develop on a

global basis. The European Monetary System arose in
particular economic and political circumstances; the
wide chasms that exist in policy preferences and economic situations between the United States, Japan, and
the European Monetary System members make it unlikely that the present era of floating, highly variable
exchange rates will end in the foreseeable future.

Notes
1. These strains are described at length in Solomon (1977).
2. Under the Bretton Woods system, governments agreed on
par values for their exchange rates and were obligated to intervene to ensure that exchange rates in the markets would
deviate no more than 1 percent from the par values.
3. Nurkse (1944) argued that floating exchange rales would be
extremely volatile, as (in his view) they were during the
1920s, thereby disrupting international trade; Roosa (1967)
and Einzig (1970) expressed similar sentiments.
4. The Canadian experience is discussed in Wonnacott (1965),
Yeager (1966, chap. 24), and Sohmen (1969, 225-37).
5. The statistics that have been used to measure exchange rate
volatility include the standard deviation of p e r c e n t a g e
changes, the mean absolute percentage change, and the percentage deviation from trend.
6. This view is implicit in the writings of the advocates of a
flexible exchange rate regime, among them Johnson (1972),
Haberler (1970), and Friedman (1953).
7. If the investor were risk-averse and the only source of risk
was the possibility of exchange rate changes, he or she
would seek, in equilibrium, a return of more than $108.00
on the French bond, the excess being the compensation for
bearing the risk. In practice this risk premium appears to be
large and volatile. The open interest parity condition does
not include the risk premium and does not perform particularly well in empirical tests. However, it provides a convenient framework for illustrating the role of expectations in
exchange rate determination.
8. If a large share of national output is nontradable the consumer price and G N P deflator inflations can diverge significantly from wholesale or producer price inflations; the
latter two variables are heavily i n f l u e n c e d by tradable
goods prices. The question of which particular inflation

variable is conceptually more consistent with the spirit of
purchasing-power parity theory is unsettled. Frenkel (1976)
provides a discussion of this issue.
9. Dornbusch (1976) provides an "overshooting" m o d e l in
which he argues that, if goods prices adjust sluggishly but
financial markets clear instantly and people have rational
expectations, then, following a monetary shock, exchange
rates will first overshoot their long-run value before reversing course. Consequently, exchange rate variations in excess of price variations would be expected.
10. Under certain conditions it is possible for one country to
improve its welfare by imposing the so-called "optimum
tariff." However, the gain to one country is less than the
loss to the other, resulting in a loss of welfare to the world
as a whole. Moreover, the possibility of retaliation makes it
less likely that any country can gain by imposing tariffs.
See Grubel (1981, 150-53).
11. Sometimes exporters agree to take payment in the importing
country's currency. In the example in the text the U.S. exporter would then do the currency conversion, which is necessary to e n a b l e p a y m e n t to w o r k e r s and s u p p l i e r s in
dollars, and the exporter bears the exchange rate risk. Exchange rate risk is not eliminated by this procedure but
merely transferred from the importing company to the exporter.
12. Recent d e v e l o p m e n t s in e c o n o m i c theory challenge the
common conclusion that increases in exchange risk cause
reductions in trade volume in all circumstances. For instance, De Grauwe (1988) shows that if firms have constant
relative (not absolute) risk aversion, increased variability of
exchange rates may raise the marginal utility of exporting
even as it lowers total utility, leading to more exports, not
fewer.

References
Akhtar, M. Akbar, and R. Spence Hilton. "Exchange Rate Uncertainty and International Trade: Some Conceptual Issues
and New Estimates for Germany and the United States."
Federal Reserve Bank of New York Research Paper 8403,
May 1984.

Federal Reserve B a n k of Atlanta



Bailey, Martin J., George S. Tavlas, and Michael Ulan. "Exchange Rate Variability and Trade Performance: Evidence
for the Big Seven Industrial Countries."
Welrwirtschaftliches Archiv 122, no. 3 (1986): 466-77.

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Cumby, Robert E., and Maurice Obstfeld. "International Interest Rate and Price Level Linkages under Flexible Exchange
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Cushman, David O. "The Effects of Real Exchange Rate Risk
on International Tradq." Journal of International
Economics
15 (August 1983): 45-63.
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the Floating Period." Journal of International Economics 24
(May 1988): 317-30.
De Grauwe, Paul. "Exchange Rate Variability and the Slowdown in Growth of International Trade." International
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Dornbusch, Rudiger. "Expectations and Exchange Rate Dynamics." Journal of Political Economy 84, no. 6 (1976):
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Einzig, Paul. The Case against Floating Exchanges. London:
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Frenkel, Jacob A. " A Monetary Approach to the Exchange
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Grubel, Herbert C. International Economics. Rev. ed. Homewood, 111.: Richard D. Irwin, Inc., 1981.
H a b e r l e r , G o t t f r i e d . " T h e International M o n e t a r y S y s t e m :
S o m e R e c e n t D e v e l o p m e n t s and D i s c u s s i o n s . " In Approaches to Greater Flexibility of Exchange Rates, edited
by George N. Halm. Princeton, N.J.: Princeton University
Press, 1970.

national T r a d e . " Journal of International
Economics
8
(November 1978): 483-511.
International Monetary Fund. Exchange Rate Volatility
and
World Trade. IMF Research Department Occasional Paper
No. 28, 1984.
Johnson, Harry G. "The Case for Flexible Exchange Rates." In
Further Essays in Monetary Economics, edited by Harry G.
Johnson. London: George Allen and Unwin, 1972.
Kenen, Peter B., and Dani Rodrik. "Measuring and Analyzing
the E f f e c t s of S h o r t - T e r m Volatility in Real E x c h a n g e
Rates." Princeton University, International Finance Section
Working Paper G-84-01, March 1984.
. "Measuring and Analyzing the Effects of Short-Term
Volatility in Real Exchange Rates." Review of Economics
and Statistics 58 (May 1986): 311-15.
McKinnon, Ronald I. "Monetary and Exchange Rate Policies
for International Financial Stability: A Proposal." Journal of
Economic Perspectives 2 (Winter 1988): 83-103.
Meese, Richard. "Currency Fluctuations in the Post-Bretton
Woods Era." Journal of Economic Perspectives 4 (Winter
1990): 117-34.
, and Kenneth Rogoff. "Empirical Exchange Rate Models
of the Seventies: Do They Fit out of Sample?" Journal of
International Economics 14 (February 1983): 3-24.
Mussa, Michael. " T h e Exchange Rate, the Balance of Payments, and Monetary and Fiscal Policy under a Regime of
Controlled Floating." Scandinavian Journal of Economics
78 (May 1976): 229-48.
Nurkse, Ragnar. International Currency Experience. Geneva:
League of Nations, 1944.
Roosa, Robert V. "Second Lecture." In The Balance of Payments: Free versus Fixed Exchange Rates, edited by Milton
Friedman and Robert V. Roosa, 27-67. Washington, D.C.:
American Enterprise Institute for Public Policy Research,
1967.
Sohmen, Egon. Flexible Exchange Rates. Rev. ed. Chicago:
University of Chicago Press, 1969.
Solomon, Robert. The International Monetary System, 19451976. New York: Harper and Row, 1977.
Thursby, Jerry G., and Marie C. Thursby. "Bilateral Trade
Flows, the Linder Hypothesis, and Exchange Risk." Review
of Economics and Statistics 69 (1987): 488-95.
Whitt, Joseph A., Jr. "Flexible Exchange Rates: An Idea Whose
Time Has Passed?" Federal Reserve Bank of Atlanta Economic Review 75 (September/October 1990): 2-15.
Wonnacott, Paul. The Canadian Dollar, 1948-1962. Toronto:
University of Toronto Press, 1965.
Yeager, Leland B. International
Monetary Relations:
New
York: Harper and Row, 1966.

Hooper, Peter, and Steven W. Kohlhagen. The Effect of Exchange Rate Uncertainty on the Prices and Volume of Inter-

32

Economic Review




.May/June 1992

IFWE

Commercial Bank
Profitability Rises as
Interest Margins and
Securities Sales Increase
Robert E. Goudreau

ast year's environment of declining interest rates allowed U.S. commercial banks to earn higher adjusted net interest margins and to
take profits on investment securities sales. Interest expenses declined substantially more than interest revenues, and prices for
investment securities purchased in previous years advanced as interest rates fell during 1991, particularly in the year's final quarter. Adjusted net interest margins expanded during 1991 for nearly all bank size
categories. 1 This margin advanced most for the nation's largest banks
(those with assets exceeding $1 billion) because interest expenses for this
category declined considerably, more than offsetting falling interest revenues. The nation's largest banks have added markedly, but by about the
same amount, to loan-loss provisions for three consecutive years. 2 Adjusted margins for small banks (assets under $50 million) and midsize banks
(assets greater than $50 million and no more than $500 million) increased
modestly in 1991 as additions to loan-loss provisions for these categories
diminished.

The author is an assistant
economist in the financial
section of the Atlanta Fed's
research
department.

FederalforReserve
B a n k of Atlanta
Digitized
FRASER


While adjusted net interest margins for the banking industry moved forward, it was a singular gain from sales of investment securities that accounted for much of last year's increase in returns on assets and equity for banks
across the nation (see "Commercial Banking Performance" 1991 and "Bond
Sales" 1992). All size classifications of U.S. banks benefited from profits
on securities sales, with the largest banks gaining the most. Net operating
income for the industry remained approximately the same as the preceding
year's because the increase in adjusted net interest margin was more than
offset by changes in noninterest income and expense. 3 Noninterest expenses,

Economic Reuieiv

33

strongly influenced by rising Federal Deposit Insurance Corporation (FDIC) fees, rose considerably more
than noninterest income.
Profitability for the nation's smallest banks continued to rise, with last year's return on assets exceeding
those posted by the two largest size groups. However,
returns for the smallest banks remained below figures
recorded by the industry's most consistently profitable
competitors, which during the 1987-91 period were
midsize banks. Despite the recent improvement, higher noninterest operating expenses relative to total assets continued to dampen profitability for the nation's
smallest banks. Additionally, last year's profitability
gains for the industry were broad-based as the weakest, average, and most profitable banks in most asset
classifications achieved higher returns.
Southeastern banks outperformed commercial banks
nationwide during the most recent year owing mainly
to higher profitability for the region's largest banks. 4
These banks' advance in profitability was driven by
their lower additions to loan-loss provisions, marked
decline in interest expense, and substantial gains from
investment securities sales. The smallest three categories of southeastern banks (those with assets of no
more than $100 million), however, did not fare as well
as respective national counterparts in adjusted net interest margin largely because the regional banks added
comparatively more to loan-loss provisions. The most
striking disparity between national and southeastern
profitability patterns is evident for the smallest size
class. Southeastern banks with assets totaling less than
$25 million floundered during the 1987-91 period
while overall the nation's smallest banks demonstrated
a steady improvement in profitability.
The extensive tables at the end of this article contain a substantial amount of information about bank
profitability in 1991 and preceding years. The remainder of this presentation highlights some of the more
interesting patterns that emerged or continued last
year.

Profitability at the Nation's Banks
Profitability Measures. Bank profitability can
have different meanings. For the purposes of this report the focus is on three profitability measures and
their components: adjusted net interest margin, return
on assets (ROA), and return on equity (ROE). 5 These
m e a s u r e s are described in detail in the a p p e n d i x .
Briefly, adjusted net interest margin indicates a bank's

34
Economic Review


interest revenues less interest costs as a proportion of
interest-earning assets. For this analysis, revenues are
adjusted to take into account different proportions of
tax-free interest income earned by various banks and
for credit risk. The credit risk adjustment is calculated
by subtracting a bank's annual provisions for loan
losses, which approximate expected losses, from interest earnings. Net interest margin is similar to a business's gross profit margin, differing among other ways
in that it omits earnings from fees for services provided, an increasingly important source of revenue for
the nation's largest banks.
Return on assets and return on equity are more general measures of a bank's ability to earn from its total
operation. A measure of net income as a proportion
of total assets, ROA gauges how effectively a bank
uses all of its financial and real investments to earn
interest and fees. ROE reflects how effectively a bank
is using shareholders' investments.
Profitability Patterns. The adjusted net interest
m a r g i n for U.S. c o m m e r c i a l banks a d v a n c e d last
year to 3.15 percent of interest-earning assets. (See
Tables 1-4 for data on adjusted net interest margin, interest revenue, interest expense, and loan-loss provisions by size class for the years from 1987 through
1991.) Adjusted margins for the nation's largest banks
and for the banking industry as a whole have been
limited for three years by the largest banks' sizable
additions to loan-loss provisions, which annually represented roughly 1.3 percent of interest-earning assets. T h e largest banks in the nation account for
an overwhelming majority of bank assets; therefore,
changes in their earnings performance strongly influence industrywide profitability. In 1989 these banks,
particularly the money center banks, raised loan-loss
provisions to account for anticipated losses on troubled less developed country (LDC) debt and commercial real estate loans. The largest banks continued to
add to loan-loss provisions during the past two years
because of p e r s i s t e n t d e l i n q u e n c i e s on c o m m e r cial and industrial loans and commercial real estate
loans. 6
Although well below margins for other classifications, last year's increase in adjusted net interest margin
for the nation's largest banks contributed significantly
to the overall margin expansion for the industry. Interest
expenses dropped significantly in 1991 as short-term
interest rate declines were particularly pronounced.
Banks with assets exceeding $1 billion usually experience slightly better interest earnings but markedly
higher interest expenses per dollar of interest-earning
assets than banks in any other classification. In recent

.May/June 1992

years, these banks, which raise greater proportions of
their f u n d s in the money market than other banks,
have paid interest expenses 25 percent above the average faced by banks in smaller categories. Consequently, the largest banks' interest margins, notwithstanding
additions to loan-loss provisions, would be lower than
margins earned by those in smaller asset categories.
The same pattern held true for 1991, but the interest
expense disadvantage for the largest banks dropped
last year from 25 percent to 14 percent. Accordingly,
the adjusted net interest margin for the largest banks
across the nation rose to 2.74 percent of interestearning assets from 2.60 percent the year before.
Adjusted net interest margins for small and midsize
banks increased moderately as these banks reduced
additions to loan-loss provisions during 1991. Declines in interest revenue and interest expense were
approximately equal for these banks. C o m m e r c i a l
banks with assets between $500 million and $1 billion
posted lower adjusted net interest margins because of
increased loan-loss provisions and a greater decrease
in interest revenue relative to interest expense. Last
year's interest revenue decline for this size class was
greater than all other asset classes except the largest.
Interest expenses dropped noticeably for banks in the
$500 million to $1 billion asset-size category, but the
reduction was not enough to offset diminished interest
revenues. Moreover, these larger banks' rise in nonperforming loans as a percentage of total loans last
year was surpassed only by that of the nation's largest
banks (see Table 5).
In recent years, the percentage of banks with assets
between $500 million and $1 billion that recorded
negative returns on assets has been less than the comparable proportion for banks with assets exceeding
$1 billion. For example, 12.3 percent and 13.8 percent
of banks with assets of from $500 million to $1 billion
had negative ROAs in 1991 and 1990, respectively.
Comparable respective figures of 17.7 percent and
20.0 percent for banks with assets greater than $1 billion held for 1991 and 1990.
The average performance of these two largest size
categories appears to be tied to problems of larger
banks in N e w England (consisting of Connecticut,
Maine, Massachusetts, N e w Hampshire, Rhode Island, and V e r m o n t ) and the M i d - A t l a n t i c r e g i o n
(defined here as New Jersey, New York, and Pennsylvania). For banks in these two categories about 50
percent that posted n e g a t i v e R O A s in 1990 w e r e
based in the New England and Mid-Atlantic regions,
and the proportion for 1991 was approximately 40
percent.

Federal
Digitized
for Reserve
FRASER Bank of Atlanta


Commercial banks with assets less than $25 million continued to build on a recovery that began in
1987 as they tied with banks in the $25 million to
$50 million asset-size category to record the highest
1991 adjusted net interest margin among the various
size categories. Although the smallest banks' returns
on assets (0.64 percent) exceeded returns for the two
largest size groups, their ROAs remained below figures for midsize banks, as mentioned earlier. Indeed,
midsize banks have earned substantially better returns
on assets than the smallest banks for the last two years
even though adjusted interest margins for these banks
slid below margins for the smallest banks. Comparatively larger loan-loss provisions made by the nation's
smallest banks before 1989 reduced their profitability.
However, additions to loan-loss provisions for these
banks since 1989 have been the same or markedly below provisions for midsize banks, and interest margins
during these years, irrespective of additions to loanloss provisions, have been essentially equal for the
smallest and midsize banks. Accordingly, adjusted net
interest margins for the smallest banks surpassed those
for midsize banks in 1990 and 1991, leading to the
conclusion that low returns on assets for banks with
assets less than $25 million nationwide are largely attributable to high noninterest operating e x p e n s e s .
Noninterest expenses relative to total assets for banks
in this class averaged 3.9 percent of total assets during
the 1 9 8 7 - 9 1 p e r i o d , n o t i c e a b l y e x c e e d i n g r a t i o s
logged by other asset-size classifications.
The smallest asset-size classification has diminished
with respect to the actual number of banks and in the
proportion of total banks nationally and regionally during the past five years. Banks in the nation with assets
less than $25 million totaled 4,305 in 1987 (32.7 percent of all size banks that year), and for 1991 these
banks were 2,846 in number (24.7 percent of the total)
across the country. In the Southeast the smallest bank
class had 380 institutions (24.5 percent of all southeastern banks) in 1987, and for 1991 banks in this category equaled 241 (15.3 percent of the regional total).
This category has declined in size because many of
these banks (both healthy and weak) were acquired by
or merged into larger institutions. Many other small
banks moved into larger size categories through asset
growth.
With rising delinquencies, particularly on commercial real estate and commercial and industrial loans,
n o n p e r f o r m i n g loans f o r the b a n k i n g industry increased steadily over the 1989-91 period, from 2.97
percent of total loans in 1989 to 3.76 percent last year. 7
This two-year rise is attributable to sharply increasing

Economic Reuieiv

35

nonperforming loans for the two largest size groups.
The ratio of nonperforming loans to total loans for the
nation's largest banks has risen most and stands much
higher, at 4 . 3 4 percent of total loans, than figures
posted for all other size categories, including banks with
assets between $500 million and $1 billion. Although
nonperforming loan amounts have increased across the
nation, sour commercial real estate loans held by large
banks in the Northeast during recent years have contributed greatly to rising nationwide figures. In the
West, California banks began to encounter serious repayment problems on their commercial real estate
loans in 1991. 8 On the other hand, n o n p e r f o r m i n g
loan-to-total loan ratios for each of the first three assetsize classes (banks with assets up to $100 million) generally declined throughout the 1987-91 period.
Net operating income for 1991 was roughly equal to
the preceding year's income as changes in noninterest
income and expense (see Tables 6 and 7) counterbalanced the advance in adjusted interest margin for U.S.
commercial banks. Noninterest expenses advanced
more than noninterest revenues for all asset classes, but
the net change was greatest for the nation's largest
banks. About one-quarter of the increase in noninterest
expenses for the industry represented costs associated
with higher deposit insurance premiums (see "Commercial Banking Performance" 1991). Other components of noninterest expense—wage and salary costs
and occupancy expense—remained unchanged as a
proportion of the industry's total assets. The residual
category of noninterest expenses, which includes deposit insurance premiums, moved up sharply in 1991.
A $3 billion net gain from sales of Treasuries and
other securities contributed earnings that approximated the year's increase in return on assets and equity
for commercial banks nationwide (see Tables 8 and
9). Declining interest rates in 1991 allowed banks to
take profits on these investments as securities' prices
rose during the year. Most sales were made during the
fourth quarter (see "Bond S a l e s " 1992). Although
banks of all sizes benefited from investment securities sales last year, these gains relative to total assets
of banks with assets greater than $1 billion were
about twice as large as gains posted by small and
midsize banks across the country.
Changes in return on equity closely reflected ROA
changes, but increases in capital-to-asset ratios for
most asset classifications tempered ROE gains for the
nation's commercial banks last year (see Table 10). As
in previous years, larger banks' lower capital ratios allowed them to return more on book value of equity for
every dollar of ROA. 9 Although the ROE for the na-

36
Economic Review



tion's smallest banks stands below equity returns for
all other categories, this g r o u p ' s recent history of
steady improvement suggests that small banks have
regained some of their competitive vitality, and shareholder interest may not diminish.

Southeastern Banks
Overall profitability for southeastern banks as a
group was buoyed by markedly better profitability for
the region's largest banks. Last year's returns on assets
also advanced for most other asset-size categories. 1 0
Unlike during 1990, when additions to loan-loss provisions for the largest southeastern banks matched
those of national counterparts, last year's provisions
for the region's largest bank group fell by almost onefifth to 1.08 percent of interest-earning assets. 11 (Data
on southeastern banks' profitability are in Tables 1120.) Accordingly, adjusted net interest margin for the
region's largest banks rose from 3.17 percent of interestearning assets to 3.57 percent. Returns on assets for
these banks increased from 0.41 percent to 0.60 percent, and returns on equity advanced from 6.47 percent to 8.80 percent last year. Returns were raised
significantly by gains from investment securities sales,
which equaled 0.14 percent (before taxes) of total assets and far outweighed the gains recorded by other
regional and national asset classes.
The largest southeastern banks' reduced additions
to loan-loss provisions in 1991 indicate that they may
be resolving repayment problems associated with their
nonperforming loans, particularly commercial real estate loans (see " H o w Banks Are D o i n g " 1992). In
1990 and 1991 they recorded nonperforming loanto-total loan ratios one-third below figures for their
national counterparts, and last year's rise in nonperforming loans for the largest regional banks was significantly less than the increase posted by banks in
this size category across the nation. Nonperforming
loans as a percentage of total loans, though, have increased for most regional size groups during the last
two years. Since 1989 the first five regional asset classifications have posted nonperforming loan-to-total
loan ratios that approximate national figures.
A d d i t i o n s to loan-loss p r o v i s i o n s taken by the
region's banks in the three smallest categories during 1991 surpassed those taken by their respective
national counterparts, providing the main reason that
ROAs for these banks fell short of returns registered
by the nation's banks in the same categories. Addi-

May/June 1992

tionally, the smallest regional banks experienced a
relatively greater decline in interest revenue vis-a-vis
interest expense. Profitability for the nation's smallest banks advanced to respectable levels during the
1987-91 period, but earnings performance for the region's smallest banks was quite unimpressive throughout these years partly because of higher additions to
loan-loss provisions and occasionally u n f a v o r a b l e
changes in interest revenue versus interest expense.
In 1991 the Southeast's smallest banks returned a
slim 0.20 percent on assets compared with 0.64 percent for their national counterparts. In addition, noninterest operating expenses have been extraordinarily
high and have restrained earnings performance for
these banks.
A significant part of poor returns on assets and equity for the smallest southeastern banks is traceable to a
concentration of new small banks in Florida and Georgia. The average return on assets for Florida's smallest
banks was negative for the entire 1987-91 period, and
ROA for Georgia's banks in this category dwindled to
near zero in 1991.12 Banks established in the Southeast
(and the nation) during the past five years are concentrated in Florida and Georgia. Many more de novo
banks were established in these states from 1987 to
1991 than elsewhere, including the nation's most populous states. Since January 1987, 101 and 87 new banks
have commenced operations in Florida and Georgia,
respectively. California, Texas, and New Jersey hold
distant third-, fourth-, and fifth-place positions with 57,
34, and 32 de novo bank establishments, respectively,
during the same period. Many of these banks in Florida
and Georgia have grown slowly and are recording high
noninterest expenses relative to size. Hence, their return on assets is quite low or negative. In Florida and
Georgia, respectively, 61 and 27 small banks had negative returns on assets in 1991, and slightly more than
one-half of these u n p r o f i t a b l e banks in each state
opened for business within the past five years.
Despite slight returns at the region's smallest banks,
southeastern banks as a whole recorded a 0.67 percent
return on assets compared with a 0.55 percent figure for
U.S. commercial banks. The ROA for U.S. commercial
banks was crimped by poor profitability performance
of banks in the New England and Mid-Atlantic regions. If banks of all size categories in these two
regions are excluded, last year's return on assets in all
other states was a more respectable 0.71 percent.
The region's overall gain on investment securities
as a proportion of total assets was moderately higher
than advances for the banking industry overall. Returns on assets increased for the r e g i o n ' s m i d s i z e

Federal Reserve Bank of Atlanta



banks and banks with assets between $500 million
and $1 billion. Gains on investment securities also
added appreciably to returns for these midsize and
larger banks, as well as to returns for the two smallest
southeastern bank classifications.
Southeastern states' economic performance during
the 1990-91 recession noticeably influenced bank
profitability for c o m p o n e n t states. During the late
1980s the economies of Georgia and Florida consistently outperformed other regional states', but during
the recent recession these states were the r e g i o n ' s
worst performers in terms of employment and personal income growth. Louisiana and Mississippi seemed
m o s t i m m u n e to the national d o w n t u r n while the
economies in Alabama and Tennessee closely mirrored the national economy during the last two years
(see "Southeastern Recovery Stumbles" 1991). Alabama banks, which have maintained good asset quality
and added only moderately to loan-loss provisions,
continued to lead the region in profitability with a
1.04 percent return on assets for 1991. Notable changes,
however, occurred in other southeastern states (see
Tables 21-26). Mississippi banks, which have earned
consistently respectable profits throughout the 198791 period, captured second place last year with an
ROA of 0.90 percent. Although Georgia banks had
scored the highest ROA in the Southeast in 1989 and
earlier, profitability for this state's banks ranked third
d u r i n g the most recent year. T e n n e s s e e banks rebounded from lackluster returns in 1990 by slashing
last year's additions to loan-loss provisions. Although
a d d i t i o n s to loan-loss provisions remain high f o r
Florida banks, last year's statewide reduction helped
raise the return on assets for Florida banks to 0.50
percent.
Louisiana banks, which had been awash in red ink,
recorded a 0.20 percent and 0.22 percent return on assets for 1990 and 1991, respectively. Profitability for
Louisiana banks has been modest or negative since
1986, the year in which oil prices dropped from previously robust levels. Louisiana banks, though, may
have achieved a measure of success in working out
problem loans as their returns on assets and equity
during the past two years rose through lower additions
to loan-loss provisions.

7Tie Distribution of Bank Profitability
Examining changes in overall profitability for banks
of differing profitability levels reveals certain clues

Economic Reuieiv

37

about the ways banks have responded to difficulties
facing them and other financial institutions during the
1980s and early 1990s. One way to analyze banks'
profitability distribution within a given asset-size category is to rank all its banks in ascending order of
profitability, divide the group into quartiles, and describe the profitability of the most profitable bank
in each quartile. For e x a m p l e , the bank with the
highest ROA in the first (lowest) quartile would be
the one at the 25th percentile; that is, 25 percent of
all banks in a particular size category are less profitable than the bank at the 25th percentile. The change
in profitability of the bank at the 25th percentile over
time would suggest the degree to which the least
profitable banks in that asset category are experiencing earnings improvement or deterioration. Likewise,
movements in the ROA for the bank at the 75th percentile over time would indicate changes in the earnings of the more profitable banks in that size category. A rise in profitability over time at the various
percentiles suggests improved conditions; downward
m o v e m e n t s indicate d e t e r i o r a t i o n . Tables 2 7 - 2 9
present the national profitability distribution for each
of the six asset-size categories during the past five
years.
The banks with the lowest profitability in nearly all
size classes demonstrated improved profitability in
1991. The sole exception was in the category of banks
having assets between $100 million and $500 million;
that bank's return on assets stayed the same. Last
year's proportionate advance among the least profitable banks was greatest for the largest asset class,
where ROA more than doubled from the previous
year. Return on assets for the lowest quartile banks

with assets less than $25 million and with assets between $500 million and $1 billion also increased
markedly. After declining in 1990, ROA for most 50th
percentile and 75th percentile banks in various asset
groups advanced last year. Mid- and upper-quartile
banks with assets of $500 million to $ 1 billion were the
exception as returns for these banks diminished. Like
banks in the weakest quartile, profitability among the
nation's average and most profitable banks improved
greatly for the largest banks.

Conclusion
Two major forces drove profitability of the nation's
banks in 1991. While falling interest rates brought
down both interest revenues and expenses, banks succeeded in cutting expenses by a greater amount than
revenue dropped. Banks also took advantage of declining interest rates to profit from securities sales. At
the same time that banks benefited from falling interest rates, however, increasing FDIC insurance fees
and other operating costs partially offset their gains.
Benefits related to interest rate declines may well
be cyclical, particularly gains from securities sales. Increased deposit insurance costs, on the other hand,
seem likely to be with banks for some time to come.
In addition, nonperforming loan ratios continued to
rise at banks with assets greater than $50 million.
Consequently, the improved bank profitability seen in
1991 may well be a temporary hiatus rather than a signal that the worst is over for the nation's banks.

Appendix
Profitability Measures
Three different measures have been used to provide
information on bank p e r f o r m a n c e : a d j u s t e d net interest
margin, return on assets, and return on equity. A d j u s t e d
net interest margin gauges the d i f f e r e n c e b e t w e e n a
b a n k ' s interest income and expenses and is roughly similar to a b u s i n e s s ' s gross profit margin. G r o s s profit is the
a m o u n t received from sales minus the cost of g o o d s or
services sold; other expenses such as sales, advertising,
salaries, and rent have not been deducted. For banks, this
indicator is c a l c u l a t e d by s u b t r a c t i n g interest e x p e n s e
f r o m tax-adjusted interest revenue (net of loan-loss pro-

38

Economic Review




visions) and dividing that result by net interest-earning
assets. F o r this calculation, interest r e v e n u e f r o m taxe x e m p t s e c u r i t i e s is a d j u s t e d u p w a r d b y t h e b a n k ' s
m a r g i n a l tax rate to a v o i d p e n a l i z i n g institutions that
hold substantial state and local securities portfolios,
which reduce tax burdens.
Loan-loss e x p e n s e s are subtracted f r o m interest reve n u e to place b a n k s that m a k e lower-risk loans at l o w e r
interest rates on a m o r e equal footing with c o m m e r c i a l
b a n k s that m a k e higher-risk loans, w h i c h can g e n e r a t e
greater interest i n c o m e . For e x a m p l e , interest rates on
credit c a r d s h a v e b e e n substantially h i g h e r than rates
on p r i m e c o m m e r c i a l loans, but loan losses on credit

M a y / J u n e 1992

cards h a v e also b e e n larger. C h a r g e - o f f s on credit cards
w e r e 3.4 percent of total credit card v o l u m e in 1990 f o r
the n a t i o n ' s top 100 b a n k s in credit card operations, acc o r d i n g to " T o p 100 B a n k s " (1991).
B a n k s also bring in noninterest r e v e n u e in the f o r m
of loan o r i g i n a t i o n fees; d e p o s i t s e r v i c e c h a r g e s ; and
charges for letters of credit, loan c o m m i t m e n t s , and other off-balance-sheet services, to n a m e a f e w . G a i n s f r o m
sales of s e c u r i t i e s also p r o v i d e a d d e d i n c o m e . M o r e over, b a n k s incur noninterest e x p e n s e s such as expenditures on e m p l o y e e salaries, c o m p u t e r e q u i p m e n t , a n d
m a i n t e n a n c e . T h e r e f o r e , B a n k X with a comparatively
low a d j u s t e d interest margin m a y a c h i e v e a higher return on assets than Bank Y, w h i c h attained a larger m a r g i n . T h a t is, B a n k X m a y r e c o r d a h i g h e r r e t u r n on
assets by realizing higher noninterest revenues or l o w e r
noninterest expenses.
T h e return on assets ( R O A ) ratio—the result of dividing a b a n k ' s net income by its a v e r a g e a s s e t s — g a u g e s
h o w well a b a n k ' s m a n a g e m e n t is using the f i r m ' s assets. T h e return on equity ( R O E ) f i g u r e tells a b a n k ' s
shareholders h o w m u c h t h e institution is e a r n i n g on the
b o o k v a l u e of their investments. R O E is calculated by
dividing a b a n k ' s net i n c o m e by its total equity. T h e ratio of R O A to R O E falls as the b a n k ' s capital-to-assets
ratio rises. S m a l l e r b a n k s typically h a v e h i g h e r capitalto-assets ratios.
A n a l y s t s w h o w a n t to c o m p a r e p r o f i t a b i l i t y w h i l e
ignoring d i f f e r e n c e s in equity capital ratios tend to f o c u s on R O A . P e o p l e w i s h i n g to f o c u s o n r e t u r n s t o
s h a r e h o l d e r s l o o k at R O E . H i g h l y c a p i t a l i z e d b a n k s
that post t h e s a m e return o n assets as less well c a p i t a l ized c o m p e t i t o r s will record a l o w e r return on equity.
B e c a u s e r e t u r n o n e q u i t y is c o m p u t e d by d i v i d i n g a
b a n k ' s net i n c o m e by its capital reserve, a b a n k ' s ret u r n o n e q u i t y will d e c l i n e as its c a p i t a l r e s e r v e increases, a s s u m i n g net i n c o m e r e m a i n s f i x e d .

Federal Reserve B a n k of Atlanta



Profitability Data and Calculations
T h e data in this article are taken f r o m reports of condition and income filed with federal bank regulators by
insured c o m m e r c i a l b a n k s . T h e s a m p l e c o n s i s t s of all
banks that had the s a m e identification n u m b e r at the beginning and end of each year. T h e n u m b e r of b a n k s in
the 1991 s a m p l e is 11,519.
T h e three profitability measures used in this study are
d e f i n e d as follows:
A d j u s t e d Net Interest Margin =
Expected Interest R e v e n u e s - Interest E x p e n s e
A v e r a g e Interest-Earning Assets
Return o n Assets =
Net Income
A v e r a g e Consolidated Assets
Return on Equity =
Net Income
A v e r a g e Equity Capital
A v e r a g e interest-earning assets, consolidated assets,
and equity capital are derived by averaging beginning-,
middle-, and e n d - o f - y e a r b a l a n c e sheet figures. T h e expected interest i n c o m e c o m p o n e n t to net interest margin
incorporates t w o significant a d j u s t m e n t s f r o m ordinary
interest income. If profits b e f o r e tax are greater than zero, the lesser of revenue f r o m state and local securities
e x e m p t from federal tax or the b a n k ' s profits b e f o r e tax
is divided by 1 m i n u s t h e b a n k ' s m a r g i n a l federal tax
rate. L o a n - l o s s e x p e n s e s a r e s u b t r a c t e d f r o m interest
revenue.

Economic Reuieiv

39

Table 1
Adjusted Net Interest Margin as a Percentage of Interest-Earning Assets
(Insured commercial banks by consolidated assets)
Year

All
Banks

$0-$25
million

$25-$50
million

$50-$ 100
million

$100-$ 500
million

$500 millionS i billion

$1 bill ion-f-

1987

2.65

3.75

3.89

4.07

4.15

3.85

1.98

1988

3.74

4.03

4.15

4.26

4.26

3.85

3.55

1989

3.13

4.24

4.32

4.38

4.38

4.17

2.61

1990

3.06

4.26

4.24

4.23

4.11

3.97

2.60

1991

3.15

4.29

4.29

4.25

4.14

3.70

2.74

S o u r c e : Figures in all tables have been computed by the Federal Reserve Bank of Atlanta from data in "Consolidated Reports of C o n d i t i o n for
Insured C o m m e r c i a l B a n k s " and "Consolidated Reports of i n c o m e for Insured C o m m e r c i a l Banks/' 1987-91, filed w i t h e a c h bank's
respective regulator.

Table 2
Tax-Equivalent Interest Revenue as a Percentage of Interest-Earning Assets
(Insured commercial banks by consolidated assets)
Year

All
Banks

$0-$25
million

$25-$50
million

$50-$ 100
million

$100-$ 500
million

$500 millionS i billion

$1 billion+

1987

9.84

9.78

9.86

9.89

9.97

9.98

9.81

1988

10.68

10.11

10.17

10.26

10.33

10.34

10.87

1989

11.67

10.76

10.91

10.96

11.20

11.31

11.90

1990

11.28

10.59

10.68

10.67

10.79

11.13

1991

11.49

10.06

9.86

10.00

9.99

10.03

9.95

10.09

Table 3
Loan-Loss Expense as a Percentage of Interest-Earning Assets
(Insured commercial banks by consolidated assets)

40

Year

All
Banks

$0-$25
million

$25-$50
million

$50-$ 100
million

$100-$500
million

$500 millionS i billion

$1 billion+

1987

1.49

0.92

0.81

0.68

0.69

0.90

1988

1.84

0.65

0.72

0.63

0.57

0.59

0.79

1989

0.66

1.11

0.59

0.56

0.50

0.59

0.69

1990

1.33

1.11

0.49

0.50

0.50

0.66

0.98

1991

1.31

1.17

0.40

0.44

0.47

0.63

1.07

1.40




Economic Review
M a y / J u n e 1992

Table 4
Interest Expense as a Percentage of Interest-Earning Assets
(Insured commercial banks by consolidated assets)
Year

All
Banks

$0-$25
million

$25-$50
million

$50-$ 100
million

$100-$ 500
million

$500 millionS i billion

$1 billion+

1987

5.71

5.11

5.16

5.14

5.13

5.23

5.98

1988

6.29

5.36

5.39

5.43

5.47

5.69

6.66

1989

7.43

5.93

6.04

6.07

6.23

6.45

7.96

1990

7.11

5.83

5.94

5.93

6.00

6.19

7.58

1991

5.73

5.17

5.26

5.26

5.26

5.19

5.95

Table 5
Nonperforming Loans as a Percentage of Total Loans
(Insured commercial banks by consolidated assets)
Year

All
Banks

$0-$25
million

$25-$50
million

$50-$ 100
million

$100-$ 500
million

$500 millionS i billion

$1 billion+

1987

3.63

3.63

3.10

2.72

2.27

2.48

4.08

1988

3.11

2.98

2.66

2.31

2.01

2.52

3.44

1989

2.97

2.59

2.31

2.10

1.96

2.09

3.32

1990

3.38

2.25

2.14

2.01

2.05

2.32

3.85

1991

3.76

2.12

2.08

2.03

2.19

2.73

4.34

Table 6
Noninterest Income as a Percentage of Total Assets
(Insured commercial banks by consolidated assets)
Year

All
Banks

$0-$25
million

$25-$50
million

$50-$ 100
million

$100-$ 500
million

$500 millionS i billion

$1 billion+

1987

1.39

0.97

0.76

0.74

0.92

1.13

1.62

1988

1.44

0.91

0.75

0.82

0.90

1.12

1.68

1989

1.52

1.08

0.78

0.86

0.98

1.11

1.76

1990

1.64

1.09

0.82

0.83

0.94

1.26

1.91

1991

1.73

1.09

0.85

0.88

1.05

1.24

2.02

Federal
Reserve B a n k of Atlanta



Economic Reuieiv

41

Table 7
Total Noninterest Expense as a Percentage of Total Assets
(Insured

commercial

banks

by consolidated

assets)

Year

All
Banks

$0-$25
million

$25-$50
million

$50-$ 100
million

$100-$ 5 00
million

$500 millionS i billion

$1 billion+

1987

3.34

3.87

3.39

3.24

3.32

3.58

3.31

1988

3.37

3.84

3.39

3.31

3.36

3.49

3.35

1989

3.39

3.86

3.41

3.31

3.40

3.34

3.39

1990

3.50

3.94

3.45

3.32

3.34

3.54

3.53

1991

3.73

3.99

3.56

3.39

3.47

3.59

3.81

Table 8
Securities Gains (Losses) before Taxes as a Percentage of Total Assets*
(Insured

commercial

banks

by consolidated

assets)

Year

All
Banks

$0-$25
million

$25-$50
million

$50-$ 100
million

$100-$ 500
million

$500 millionS i billion

$1 billion+

1987

0.05

0.02

0.03

0.03

0.04

0.04

0.05

1988

0.01

0.00

(0.00)

0.01

0.01

0.00

0.01

1989

0.02

0.00

0.01

0.01

0.01

(0.00)

0.03

1990

0.01

0.00

0.00

0.00

(0.00)

0.01

0.02

1991

0.09

0.04

0.05

0.05

0.06

0.07

0.10

$1 billion+

*0.00 indicates

securities gains (losses) that are less than 0.01 percent

of total assets.

Table 9
Percentage Return on Assets
(Insured

commercial

banks

by consolidated

assets)

Year

All
Banks

$0-$25
million

$25-$50
million

$50-$ 100
million

:!>100-$500
million

$500 millionS i billion

1987

0.09

0.26

0.46

0.66

0.73

0.51

-0.15

1988

0.83

0.36

0.61

0.77

0.80

0.58

0.89

1989

0.50

0.60

0.73

0.88

0.91

0.88

0.35

1990

0.50

0.60

0.71

0.81

0.79

0.77

0.39

1991

0.55

0.64

0.75

0.86

0.85

0.56

0.45

42
Economic



Review

M a y / J u n e 1992

Table 10
Percentage Return on Equity
(Insured commercial banks by consolidated assets)

Year

All
Banks

$0-$25
million

$2 5-$ 50
million

$50-$ 100
million

$100-$500
million

$500 millionS i billion

1987

1.49

2.75

5.39

8.02

9.93

7.51

-2.80

1988

13.51

3.79

6.96

9.15

10.53

8.67

16.40

1989

7.85

6.15

8.14

10.12

11.81

12.72

6.21

1990

7.81

6.02

7.81

9.29

10.14

10.37

6.86

1991

8.21

6.46

8.10

9.68

10.78

7.85

7.49

$1 billion+

Table 11
Adjusted Net Interest Margin as a Percentage of Interest-Earning Assets
(Insured commercial banks in the Southeast by consolidated assets)

Year

All SE
Banks

$0-$25
million

$25-$50
million

$50-$ 100
million

$100-$500
million

$500 millionS i billion

$1 billion+

1987

4.23

4.13

4.24

4.38

4.44

3.58

4.21

1988

4.34

4.30

4.27

4.35

4.39

4.14

4.35

1989

3.92

4.20

4.37

4.33

4.35

3.61

3.73

1990

3.56

4.12

4.30

4.15

4.17

4.05

3.17

1991

3.81

4.02

4.20

4.21

4.21

3.92

3.57

Table 12
Tax-Equivalent Interest Revenue as a Percentage of Interest-Earning Assets
(Insured commercial banks in the Southeast by consolidated assets)
$100-$500
million

$500 million$1 billion

$1 billion+

10.25

10.14

9.95

10.23

10.55

10.52

10.43

10.42

10.75

11.31

11.37

11.24

11.17

11.14

11.26

10.91

10.87

11.01

10.90

10.86

11.41

10.85

9.97

9.98

10.28

10.21

10.09

9.94

9.87

Year

All SE
Banks

$0-$25
million

1987

10.20

10.21

10.30

1988

10.64

10.55

1989

11.24

1990
1991

Federal
Reserve B a n k of Atlanta



$25-$50
million

$50-$ 100
million

Economic Reuieiv

43

Table 13
Loan-Loss Expense as a Percentage of Interest-Earning Assets
(Insured commercial banks in the Southeast by consolidated assets)

Year

All SE
Banks

$0-$25
million

$25-$50
million

$50-$100
million

$100-$500
million

$500 millionS i billion

$1 billion+

1987

0.81

0.97

0.87

0.69

0.69

1.21

0.80

1988

0.65

0.71

0.69

0.58

0.63

0.56

0.67

1989

0.79

0.84

0.62

0.53

0.60

0.96

0.88

1990

1.07

0.75

0.56

0.62

0.66

1.04

1.31

1991

0.90

0.62

0.59

0.61

0.61

0.76

1.08

Table 14
Interest Expense as a Percentage of Interest-Earning Assets
(Insured commercial banks in the Southeast by consolidated assets)
Year

All SE
Banks

$0-$25
million

$25-$50
million

$50-$ 100
million

$100-$ 500
million

$500 millionS i billion

$1 billion+

1987

5.17

5.11

5.19

5.19

5.01

5.16

5.21

1988

5.65

5.54

5.59

5.60

5.41

5.72

5.73

1989

6.53

6.27

6.38

6.37

6.22

6.57

6.65

1990

6.28

6.01

6.16

6.13

6.03

6.31

6.38

1991

5.26

5.34

5.49

5.40

5.27

5.25

5.22

Table 15
Nonperforming Loans as a Percentage of Total Loans
(Insured commercial banks in the Southeast by consolidated assets)

44

Year

All SE
Banks

$0-$25
million

$25-$50
million

$50-$ 100
million

$100-$ 5 00
million

$500 millionS i billion

$1 billion+

1987

2.22

3.04

2.81

2.79

2.41

3.23

1.88

1988

1.90

2.53

2.53

2.29

2.08

2.47

1.67

1989

1.89

2.50

2.19

1.93

1.99

2.52

1.75

1990

2.43

2.31

2.16

2.05

2.14

2.46

2.57

1991

2.58

2.33

2.22

2.05

2.13

2.50

2.81

Economic



Review

M a y / J u n e 1992

Table 16
Securities Gains (Losses) before Taxes as a Percentage of Total Assets*
(Insured commercial banks in the Southeast by consolidated assets)

Year

All SE
Banks

$0-$25
million

$25-$50
million

$50-$100
million

$100-$500
million

$500 million$1 billion

$1 billion+

1987

0.03

0.01

0.02

0.02

0.03

0.05

0.03

1988

0.02

(0.01)

0.00

0.01

0.01

0.02

0.02

1989

0.03

(0.00)

0.01

0.01

(0.00)

0.00

1990

0.02

0.00

(0.00)

(0.01)

(0.01)

0.01

0.03

1991

0.11

0.07

0.06

0.05

0.07

0.04

0.14

* 0.00 indicates

securities

gains (losses) that are less than 0.01 percent

-

0.04

of total assets.

Table 17
Noninterest Income as a Percentage of Total Assets
(Insured commercial banks in the Southeast by consolidated assets)

Year

All SE
Banks

$0-$25
million

$25-$50
million

$50-$100
million

$100-$ 500
million

$500 million$1 billion

$1 billion+

1987

1.24

2.15

0.81

0.87

1.01

1.33

1.36

1988

1.22

1.40

0.86

1.09

1.04

1.25

1.31

1989

1.18

1.50

0.85

1.05

1.07

1.35

1.23

1990

1.27

1.38

0.91

1.06

1.09

1.12

1.39

1991

1.35

2.04

0.90

1.15

1.17

1.19

1.48

Table 18
Total Noninterest Expense as a Percentage of Total Assets
(Insured commercial banks in the Southeast by consolidated assets)

Year

All SE
Banks

$0-$25
million

$25-$50
million

$50-$ 100
million

$100-$ 500
million

$500 million$1 billion

$1 billion+

1987

3.61

5.11

3.59

3.45

3.53

3.83

3.58

1988

3.61

4.59

3.71

3.59

3.59

3.56

3.59

1989

3.48

4.72

3.64

3.46

3.53

3.62

3.41

1990

3.54

4.79

3.69

3.58

3.48

3.71

3.49

1991

3.72

5.30

3.74

3.72

3.59

3.60

3.74

Federal
Reserve Bank of Atlanta



Economic Reuieiv

45

Table 19
Percentage Return on Assets
(Insured commercial banks in the Southeast by consolidated assets)
Year

All SE
Banks

$0-$25
million

$25-$50
million

$50-$ 100
million

$100-$ 500
million

$500 millionS i billion

$1 billion+

1987

0.77

0.31

0.52

0.73

0.78

0.45

0.86

1988

0.82

0.30

0.51

0.81

0.78

0.86

0.87

1989

0.67

0.20

0.64

0.89

0.85

0.55

0.62

1990

0.53

0.05

0.64

0.71

0.81

0.65

0.41

1991

0.67

0.20

0.61

0.78

0.89

0.68

0.60

Table 20
Percentage Return on Equity
(Insured commercial banks in the Southeast by consolidated assets)

Year

All SE
Banks

$0-$25
million

$25-$50
million

$50-$ 100
million

1987

11.14

2.82

5.70

8.61

1988

11.60

2.80

5.48

1989

9.52

1.79

1990

7.30

1991

9.04

$100-$ 500
million

$500 millionS i billion

$1 billion+

10.27

6.90

13.99

9.41

10.18

12.85

13.71

6.71

9.98

10.99

8.29

9.79

0.39

6.77

8.00

10.36

7.65

6.47

1.76

6.40

8.70

11.33

9.77

8.80

Table 21
Adjusted Net Interest Margin as a Percentage of Interest-Earning Assets
(Insured commercial banks in the Southeast by state)
Year

All SE
Banks

Alabama

Florida

Georgia

Louisiana

Mississippi

Tennessee

1987

4.23

4.49

4.27

4.93

2.95

4.33

4.18

1988

4.34

4.46

4.39

4.98

3.38

4.20

4.10

1989

3.92

4.15

3.84

4.74

2.89

4.00

3.66

1990

3.56

4.10

3.19

4.29

3.05

3.86

3.37

1991

3.81

4.22

3.58

4.20

3.07

4.18

3.91

46
Econom ic Review



May/June 1992

Table 22
Tax-Equivalent Interest Revenue as a Percentage of Interest-Earning Assets
(Insured commercial banks in the Southeast by state)

Year

All SE
Banks

Alabama

Florida

Georgia

1987

10.20

10.06

10.08

1988

10.64

10.61

1989

11.24

1990
1991

Louisiana

Mississippi

Tennessee

11.04

9.80

10.20

9.99

10.47

11.20

10.54

10.33

10.59

11.20

11.00

12.01

10.89

11.04

11.28

10.91

10.80

10.70

11.39

10.48

10.74

11.31

9.97

10.06

9.83

10.51

9.34

9.93

9.97

Table 23
Loan-Loss Expense as a Percentage of Interest-Earning Assets
(Insured commercial banks in the Southeast by state)

Year

All SE
Banks

Alabama

Florida

Georgia

Louisiana

Mississippi

Tennessee

1987

0.81

0.44

0.77

0.73

1.59

0.60

0.65

1988

0.65

0.32

0.59

0.55

1.29

0.46

0.74

1989

0.79

0.42

0.79

0.58

1.51

0.52

0.96

1990

1.07

0.47

1.22

0.98

1.23

0.63

1.35

1991

0.90

0.54

1.03

0.95

1.11

0.49

0.79

Table 24
Interest Expense as a Percentage of Interest-Earning Assets
(Insured commercial banks in the Southeast by state)

Year

All SE
Banks

Alabama

Florida

Georgia

Louisiana

Mississippi

Tennessee

1987

5.17

5.13

5.03

5.38

5.26

5.26

5.16

1988

5.65

5.83

5.48

5.68

5.87

5.66

5.75

1989

6.53

6.64

6.38

6.69

6.49

6.51

6.67

1990

6.28

6.23

6.29

6.12

6.20

6.25

6.59

1991

5.26

5.30

5.23

5.36

• 5.15

5.26

5.28

Federal Reserve B a n k of Atlanta



Economic Reuieiv

47

Table 25
Percentage Return on Assets
(Insured commercial banks in the Southeast by state)

Year

All SE
Banks

Alabama

Florida

Georgia

1987

0.77

1.08

0.75

1.13

1988

0.82

1.16

0.78

1989

0.67

1.01

1990

0.53

1991

0.67

Louisiana

Mississippi

Tennessee

-0.07

0.87

0.89

1.15

0.03

0.85

0.85

0.61

1.08

-0.13

0.78

0.60

1.03

0.28

0.93

0.20

0.71

0.42

1.04

0.50

0.87

0.22

0.90

0.77

Mississippi

Tennessee

Table 26
Percentage Return on Equity
(Insured commercial banks in the Southeast by state)

Year

All SE
Banks

1987

11.14

1988

Alabama

Florida

Georgia

13.28

12.04

16.11

-0.93

11.46

12.31

11.60

14.39

12.14

15.78

0.36

10.94

11.62

1989

9.52

12.56

9.54

14.46

-1.86

9.88

8.23

1990

7.30

13.08

4.25

11.32

2.94

9.17

5.75

1991

9.04

13.53

7.31

10.06

3.28

11.67

10.64

Louisiana

Table 27
Percentage Return on Assets
25th Percentile According to Profitability
(Insured commercial banks by consolidated assets)

48

Year

All
Banks

1987

0.09

1988

$0-$25
million

$25-$50
million

$50-$ 100
million

$100-$ 500
million

$500 million$1 billion

$1 billion+

-0.03

0.35

0.52

0.58

0.47

0.30

0.83

0.20

0.53

0.64

0.70

0.56

0.71

1989

0.50

0.37

0.58

0.70

0.76

0.64

0.50

1990

0.50

0.36

0.53

0.63

0.65

0.41

0.10

1991

0.55

0.46

0.56

0.68

0.65

0.54

0.22




Economic Review

. M a y / J u n e 1992

Table 28
Percentage Return on Assets
50th Percentile According to Profitability
(Insured commercial banks by consolidated assets)

Year

All
Banks

$0-$25
million

$25-$50
million

$50-$ 100
million

$100-$500
million

$500 million$1 billion

$1 billion+

1987

0.09

0.67

0.84

0.92

0.96

0.94

0.86

1988

0.83

0.78

0.93

0.98

1.04

1.00

1.02

1989

0.50

0.84

0.98

1.04

1.07

1.06

0.96

1990

0.50

0.82

0.93

0.98

1.01

0.98

0.74

1991

0.55

0.86

0.95

1.00

1.01

0.94

0.81

Table 29
Percentage Return on Assets
75th Percentile According to Profitability
(Insured commercial banks by consolidated assets)

Year

All
Banks

$0-$25
million

$25-$50
million

$50-$100
million

$100-$500
million

$500 millionS i billion

$1 billion+

1987

0.09

1.09

1.18

1.25

1.24

1.20

1.08

1988

0.83

1.14

1.24

1.28

1.33

1.29

1.21

1989

0.50

1.20

1.28

1.34

1.35

1.30

1.20

1990

0.50

1.16

1.23

1.26

1.28

1.30

1.12

1991

0.55

1.18

1.24

1.27

1.28

1.25

1.16

Federal
Digitized
for Reserve
FRASERB a n k of Atlanta


Economic Reuieiv

49

Notes
1. Six size categories of commercial banks are analyzed in
this study. They are (1) banks with total assets of no more
than $25 million, (2) banks with total assets exceeding
$25 million and at most $50 million, (3) banks with total
assets greater than $50 million and no more than $100 million, (4) banks with total assets exceeding $100 million,
up to $500 million, (5) banks with total assets exceeding
$500 million and at most $1 billion, and (6) banks with total assets greater than $1 billion.
Only banks that have been opened to the public for at
least one full year are included in this study. The ratios
displayed are full-year profitability figures based on beginning-, middle-, and end-of-year balance sheets and inc o m e s t a t e m e n t s . B a n k s that c o m m e n c e o p e r a t i o n s
during any particular year will be missing beginning-ofyear data and perhaps more. See Table A on the following page.
2. A loan-loss provision is a noncash expense item charged
to a bank's earnings when expanding the allowance for
possible bad debt. These provisions are reported on a
bank's income statement. A bank does not set aside funds
(cash) in reserve to cover its loan losses, and an increase
in the loan-loss a c c o u n t does not directly c a u s e any
change in the allocation of a bank's assets.
An increase in loan-loss provisions reduces the net
value of the bank's loans on its accounting records and its
net income. Increases in provisions will also have a negative impact on a bank's equity capital as reported in its
accounting records (additions to loan-loss provisions are
subtracted from bank equity) and may trigger regulatory
demands for additional equity. See Wall (1988, 39-41).
3. Noninterest income is net income derived from fee-based
banking services, such as corporate cash management,
check collection, and c o n s u m e r annual fees on credit
cards, as well as monthly service charges on deposit accounts. Also included are many new activities, such as
fees from participations in mutual fund commissions, investment advisor fees in merger and acquisition activities,
and securities underwriting fees.
Noninterest expenses are the fixed operating costs of a
bank. They include salaries, rental of equipment, leases
of buildings and equipment, deposit insurance costs, and
taxes and other related expenses.
"Consolidated Reports of Income for Insured Commercial Banks" filed by banks with their primary regulators have three noninterest expense components. They are
(1) salaries and e m p l o y e e b e n e f i t s , (2) e x p e n s e s f o r
premises and fixed assets, and (3) other noninterest expenses. Salaries and employee benefits account for almost half the total, expenses for premises and fixed assets
absorb approximately 15 percent, and other noninterest
costs equal about 40 percent of the total.
4. In this study Southeast refers to the six states entirely
or partially within the Sixth Federal Reserve District:

50
Economic Review



Alabama, Florida, Georgia, Louisiana, Mississippi, and
Tennessee.
5. The revenue, expense, and profitability figures presented
are generally similar to those displayed in prior bank
profitability studies published in the Economic
Review
(see Goudreau and King 1991 for the most recent study).
The figures may not be identical because the data have
been corrected for reporting errors. Additionally, the interest revenue as a percentage of interest-earning assets
ratio and adjusted net interest margins may differ from
figures reported in previous studies because of corrections in the treatment of tax-exempt interest income.
6. Loan problems worsened in 1990, with the bulk of troubled loans shifting generally from sour commercial real
estate lending in the Southwest. The 1990 deterioration
was greatest in commercial real estate loans across the
nation, although larger banks in the Northeast were hit
hardest. The Northeast and other regions also experienced
rising delinquencies on commercial and industrial loans.
See " C o m m e r c i a l B a n k i n g P e r f o r m a n c e " (1990,
1991). Commercial and industrial (C&I) loans are made
to corporations, commercial enterprises, or joint ventures,
as opposed to loans to consumers. C&I loans can be a
source of working capital or used to finance the purchase
of manufacturing plants and equipment.
7. In this study, nonperforming loans are defined as loans
past due 90 days or more and nonaccrual assets. Total
nonperforming loans are expressed as a percentage of total loans.
A nonaccrual asset is usually a loan that is not earning the contractual rate of interest in the loan agreement
owing to financial difficulties of the borrower. Nonaccrual assets are loans for which interest accruals have been
suspended because full collection of principal is in doubt
or because interest payments have not been made for a
sustained period of time.
8. Accordingly, California banks made significant additions
to loan-loss provisions during the O c t o b e r - D e c e m b e r
quarter to account for anticipated losses. See "Commercial Banking Performance" (1991) and "How Banks Are
Doing" (1992).
9. Equity-to-assets ratios for banks in the six asset classifications during the 1987-91 period are displayed in Table B.
Equity-to-assets ratios, with few exceptions, have risen
steadily for each size group during the five years under
review. Larger banks maintain equity-to-assets ratios that
are considerably lower than smaller competitors.
10. See Table C.
11. See Table D. See "Commercial Banking Performance"
(1991) for troubled real estate loan rates for other states
and regions.
12. See Table E. Total assets for the smallest banks in Florida
and Georgia equaled 26 percent and 28 percent, respectively, of the southeastern total for 1991.

M a y / J u n e 1992

Table A
U.S. Commercial Banks, 1991
$0-$25
million

$25-$50
million

$50-$TOO
million

$100-$500
million

2,846

3,092

2,750

2,209

257

365

Percent of U.S.
Banks

24.7

26.8

23.9

19.2

2.2

3.2

Total Assets
($ billions)

44.2

108.3

188.0

444.4

173.7

2,331.9

1.3

3.3

5.7

13.5

5.3

70.9

Year
Number of Banks

Percent of U.S.
Total Assets

$500 million$1 billion

$1 billion+

Table B
Equity-to-Total Assets Ratios
U.S. Commercial Banks
(Percent)

Year

All
Banks

$0-$25
million

$25-$50
million

$50-$100
million

$100-$500
million

$500 million$1 billion

$1 billion+

1987

6.06

9.37

8.59

8.21

7.39

6.77

5.27

1988

6.17

9.41

8.82

8.44

7.56

6.72

5.43

1989

6.34

9.71

8.98

8.66

7.68

6.94

5.65

1990

6.36

9.95

9.06

8.73

7.80

7.39

5.64

1991

6.68

9.95

9.20

8.83

7.92

7.17

6.04

Table C
Southeastern Commercial Banks, 1991
$0-$25
million

$25-$50
million

$50-$ 100
million

Number of Banks

241

505

431

307

37

50

Percent of S.E.
Banks

15.3

32.1

27.4

19.5

2.4

3.2

Total Assets
($ billions)

4.0

17.6

29.3

59.5

24.7

203.9

Percent of S.E.
Total Assets

1.2

5.2

8.6

17.6

7.3

60.1

Year

Federal Reserve Bank of Atlanta



$100-$500
million

$500 million$1 billion

Economic Reuieiv

$1 billion+

51

Table D
Troubled Real Estate Asset Rates*
(December
Year

1991)

Alabama

Florida

Georgia

Louisiana

2.64

6.22

4.69

11.10

Percent

*Noncurrent

31,

real estate loans plus other real estate owned

(OREO)

as a percent

Mississippi
3.68

of total real estate loans plus

Tennessee
5.09

OREO

Table E
Southeastern Banks with Assets of $ 2 5 Million or Less
Percentage Return on Assets
(Insured commercial banks by consolidated assets)
All SE
Banks

Alabama

1987

0.31

0.90

-0.92

1.32

1988

0.30

0.84

-0.77

1989

0.20

0.62

1990

0.05

1991

0.20

Year

Florida

Georgia

Louisiana

Mississippi

Tennessee

-1.49

0.64

0.78

0.82

-0.84

0.90

0.92

-1.16

0.69

0.35

0.78

0.56

0.59

-0.94

0.33

0.43

0.56

0.19

0.21

-0.20

0.01

0.41

0.81

0.49

References
"Bond Sales Pumped Up Bank Profits Last Year."
Banker, March 12, 1992, 1,14.

American

" C o m m e r c i a l Banking P e r f o r m a n c e - F o u r t h Quarter, 1990."
FDIC Quarterly Banking Profile. Washington, D.C.: Federal Deposit Insurance Corporation, 1990.
"Commercial Banking P e r f o r m a n c e - F o u r t h Quarter, 1991."
FDIC Quarterly Banking Profile. Washington, D.C.: Federal Deposit Insurance Corporation, 1991.
Goudreau, Robert E., and B. Frank King. "Commercial Bank
Profitability: Hampered Again by Large Banks' Loan Problems." Federal Reserve Bank of Atlanta Economic
Review
76 (July/August 1991): 39-54.

52
Economic



"How Banks Are Doing across U.S. Varies from Region to Region." Banking Policy Report (The Secura Group, Washington, D.C.) 11 (February 17, 1992): 5-7.
"Southeastern Recovery Stumbles Out of the Starting Gate."
Federal Reserve Bank of Atlanta Regional Update 4 (Fall
1991): 1-4.
"Top 100 Banks in Credit Card Operations." American
Banker,
September 10, 1991, 10-A.
Wall, Larry D. "Commercial Bank Profits: Still Weak in 1987."
Federal R e s e r v e Bank of Atlanta Economic Review 73
(July/August 1988): 28-42.

Review
M a y / J u n e 1992

Edge City: Life on the New Frontier
by Joel Garreau.
New York: Doubleday, 1991.
546 pages. $22.50.

William Roberds

M

istory contains only a few individuals who have caused as
much intellectual suffering as Johann Heinrich von Thiinen.
It was Thiinen, an early nineteenth century Prussian econot
t
mist, who brought the term "marginal" into the mainstream
«.JL
of economic analysis. As any student of economics can attest, there is no economic concept more venerated by professors and reviled by students than the idea of the "margin." Those students hoping to
pass their first course in economics have to endure lectures featuring such
narcolepsy-inducing concepts as marginal costs, marginal utility, marginal
productivity, and marginal revenue.
Yet the pall cast by Thiinen's work extends well beyond the confines of
college economics courses into our everyday habits of thought. Thiinen's
idea of the margin derives from his celebrated model of an urban area. According to this theory, economic forces would cause such an area to have a
genuine city only at its core, surrounded by concentric rings of more or less
rural areas. The intensity of crop cultivation and density of population
would decrease with distance from the central city and would terminate "at
the edge of a wild and uncultivated zone," representing the outer margin of
civilization. As quaint as Thtinen's theory may sound to modern ears, this
particular abstraction still shapes our "monocentric" language of urban configurations: We still speak of "central business districts," even though they
may be neither central nor businesslike, and "suburbs" whose commercial
and manufacturing capacity often outstrips that of the central city. And too
often our private decisions and public policy debates are still couched in
such Thiinenesque terms.
!

The reviewer is a research
officer and senior economist
in the macropolicy section of
the Atlanta Fed's research
department. He thanks Dennis
Epple, Andrew Krikelas, and
Paul Wilson for their patient
assistance in preparing this
review. None of them is
responsible for any misstatements, errors, or
ill-informed opinions that
readers may discover in
the end product.

Federal Reserve B a n k of Atlanta



U
m

Economic Reuieiv

53

P e r h a p s the primary m e s s a g e of Joel G a r r e a u ' s
Edge City: Life on the New Frontier is an eloquent plea
for its readers to cast off the intellectual cobwebs of
Thiinen's theory. In 1991 there are too many Gallerias,
Silicon Valleys, Perimeter Centers, and other commercial centers (Garreau dubs them "edge cities") located
outside of traditional downtown areas for people to
speak sensibly in terms of central cities and suburbs.
However, the most enjoyable feature of Edge City is its
unique and readable collection of insights as to why so
much of the U.S. population and commerce is now
concentrated in edge cities or, in more concrete terms
(no pun intended), why in recent years so much of the
United States has started to look like Los Angeles.
One major factor contributing to the book's readability is the author's competence as a journalist. Nine
of the ten chapters of Edge City each deal with a specific U.S. metropolitan area and its various edge-city
developments. It is clear that Garreau has amassed a
goodly amount of detailed information on these metropolitan areas, but he has managed to frame each area's
situation in slightly different terms so that the presentation never becomes boring or redundant. Each chapter presents a fresh perspective on edge cities, offering
new insights to both the local and national situation.
The case of the Atlanta metro area, for example, is
used to illustrate the black middle class's participation
in the movement of commerce and population toward
the edge cities.
T h e most important characteristic of G a r r e a u ' s
analysis is the q u a s i - e c o n o m i c nature of his basic
approach. In refreshing contrast to many previous
studies, Edge City does not begin by presuming that
indoor shopping malls and the other characteristic
edge-city constructs manifest the Spenglerian decline
of Western civilization. Instead, Garreau acknowledges a number of reasons why rational people might
prefer to live and work near major shopping malls and
other edge-city developments, even though they might
also find such developments aesthetically repugnant.
He proposes that rational people might, for example,
actually prefer shorter commuting times and the (at
least perceived) mobility and status of commuting by
automobile instead of by bus or train. People might
prefer the cheaper housing and lower taxes historically
offered by areas outside the central business district.
People might prefer the security offered by a brightly
lit, glass-elevatored, security-patrolled shopping mall
to the relative insecurity of an older downtown shopping district. Garreau's point is that much of the development of edge cities is perhaps best explained as an
attack of mass rationality (seeking out edge-city ameni-

54




Economic Review

ties) as opposed to an attack of mass hysteria (escaping the "evils" of downtown). 1
Having admitted the possibility of rampant rationality in the U.S. population, economists may also admire
the analysis in Edge City for making a clear distinction
between the rationality of individuals and the desirability of market outcomes. To do this Garreau must at
least implicitly calculate an economic equilibrium,
which he does in Chapter 4. Rational people in the
United States, it turns out, do want the convenience,
low costs, and security offered by the urban periphery;
yet at the same time there has not been a stampede to
Dubuque. People want to enjoy the employment, shopping, and amusement opportunities that are typically
available only in urban areas. Garreau calculates that
a successful major retail mall, for example, needs a
quarter-million customers within a fifteen-minute drive.
And in most metropolitan areas, the price of land dictates that successful large malls will have to be multistory structures that include parking garages. The
presence of such a mall, in turn, leads to other relatively high-density development in the vicinity. According
to Garreau, this process is the essential trade-off of
edge-city developments: the density of development
necessary to bring "urban amenities" to outlying areas
tends to undermine the advantages of accessibility and
cost that initially brought development to these areas.
He reckons that the critical point for most edge cities is
reached near or before the ratio of floor space to land
area (FAR) is 1.5. Stated differently, it is very difficult
to develop edge cities in which the total area of floor
space exceeds the total area of the land by more than
50 percent. At densities higher than 1.5 FAR, competition from newer, less densely developed edge cities
makes additional growth difficult.
This point is the single most important one of the
book, and it bears repeating. For all of our newfound
ecological consciousness, most Americans do not like
to walk or use public transportation. Garreau reports
that the upper limit on walking distances in the United
States, outside of airports and the old downtowns, is
about 600 feet; any further, and most people will go by
car. Faced with the similar choice of living or working
in a congested central business district (FAR typically
5.0 or more), in a mature edge city (FAR approaching
1.5), or in a new, less congested edge-city area (FAR <
1.0), the new edge city will almost always win hands
down.
Garreau's arguments in favor of this point are tightly spun and backed with illustrative anecdotes and calculations. At the same time, he is careful not to let
these arguments degenerate into apologia. Being well

.May/June 1992

aware of the TV-villain image that our society has assigned to commercial real estate developers, he takes
great pains not to minimize the negative aspects associated with e d g e - c i t y d e v e l o p m e n t s . G a r r e a u ' s
journalistic abilities again come to the fore in his descriptions of some of the more prominent developers,
in which he skillfully manages to depict the people behind the stereotypes.
In fact, Edge City's most obvious shortcoming is
that it is a bit too impartial in its assessment of the decentralization currently going on in U.S. metro areas.
Granted, as a nation we seem to have strongly mixed
views on what is happening, and Edge City reflects
our wishy-washy state of mind. We are often outspoken in our condemnation of new development and
frequently just as outspoken on our right to live in
single-family houses on half-acre lots. Although Garreau very aptly shows how this conflict has led to the
prevalent edge-city pattern of development, one still
wants to ask where all of this is leading. Are we headed toward a new era of Jeffersonian democracy, or
does the continued construction of new and ever more
remote edge cities amount to an urbanized version of
"slash and burn" fanning?
Garreau provides us only a few clues to the answers
to these questions. First, he points out that edge cities
are fairly new and that certainly their form will continue to evolve—for the better, one may hope. After all,
he argues, even Venice was chaotic and ugly during its
rise to power. Second, Garreau goes out of his way to
point out that the form of edge cities is already changing in ways that many people would characterize as
improvements. For example, negative reactions to the
"freshly bulldozed" look of new office developments
has given birth to what he calls the "great-big-oaktrees-right-up-against-the-windows" look that is currently fashionable in office developments, together
with "hanging-gardens-of-Babylon" parking garages.
And in many edge-city communities (the book considers the case of Pasadena, California), local governments
have adopted building codes that try to discourage the
pervasive uniformity that often generates negative reactions to new edge-city areas.
Despite such efforts, Garreau's treatment of these
issues seems a bit too Panglossian. Having brilliantly
drawn the distinction between the reasonable desires
of the U.S. middle class (a three-bedroom home on a
half-acre lot) and the only partially satisfactory result
(edge cities), Garreau does not dig very deeply into
the possible economic causes of and remedies for the
perceived shortcomings of edge-city areas. An especially glaring weakness is the relative lack of treat-

Federal Reserve Bank of Atlanta



ment of public finance issues. One wonders, for example, Would the American penchant for suburban living
be nearly so strong without the usual disparity in local
tax rates between urban and suburban areas? Does the
increasingly widespread exaction by local governments of "impact fees" for new developments lead to
better-planned and more amenable edge cities, and to
what extent do such fees discourage new development? With the possible exception of the chapter on
Phoenix, Edge City is uncharacteristically mute on
such topics.

Garreau s point is that much of the development of edge cities is perhaps best
explained as an attack of mass rationality
.. .as opposed to an attack of mass hysteria.

Similar concerns extend to the arena of government
policy at the state and national levels. As an example,
one cannot seriously study the housing market as one
of the major forces behind the formation of edge cities
without seeing the highly visible hand of government
intervention. The U.S. housing industry is one of the
most regulated, taxed, and subsidized industries in the
country. Since its end product is so politically sensitive, it is unrealistic to imagine that the industry will
find itself in a laissez-faire environment at any time in
the near future. Yet it is hard to accept that a better replacement could not be found for the current unwieldy
and often contradictory amalgam of local, state, and
national laws, regulations, and policies that attempt to
influence the housing market. Unfortunately, Garreau
does not share with his readers what must be his wellinformed opinions on this subject.
One useful way of viewing such issues is from the
perspective advanced by the noted economist Charles
M. Tiebout. 2 Tiebout's theory addressed the problem
of how best to provide "local public goods"—commodities or services such as roads, water and sewer
services, and police protection that are traditionally
not priced in competitive markets but are provided by
local governments and paid for with tax revenues.

Economic Reuieiv

55

Tiebout reasoned that the presence of mobile households would provide a reasonable approximation to
the forces of a competitive market. That is, if people
were allowed to "vote with their feet" and to choose
freely among different communities with different levels of taxation and investment in local public goods,
then people would gravitate to communities that best
matched their demand for these kinds of goods.

cess of private developments in Phoenix and elsewhere in the country, it seems doubtful that the full
costs of this additional infrastructure can be entirely
privatized.
Although hard data are not available to prove the
point, the move toward edge cities seems to imply a
substitution of one sort of public good for another
rather than a fundamental change in the degree of the
public's demand for public goods. One line of thinking, consistent with Tiebout's view, is that this substitution could indicate a shift toward a wider selection
of public goods. Or it could represent, considering the
continual c o n s t r u c t i o n of new, m o r e r e m o t e edge
cities, a movement toward a single, relatively uniform
standard for the provision of public goods. Unfortunately, Garreau fails to disclose any clear sense of the
direction of what may well be a fundamental shift.

The analysis in Edge City makes clear that "voting
with your feet" has become very easy to do in the last
decade. Technology and interstate h i g h w a y s have
made it easier for people to behave in the way that
Tiebout hypothesized. People are no longer voting
only with their feet but with their car tires, computer
modems, and fax machines. Clearly, by their choice
of location, people and companies in this country are
voting for a lower level of the types of public goods
and services that are traditionally associated with
large Cities. The urban amenities of public transportation, parks, sidewalks, and the like are not enough to
lure people or their employers away from edge cities.
A s Garreau points out in his chapter on Phoenix,
many people have chosen to opt out of the domain of
local government entirely by living in private communities. Yet it is not clear that an edge-city pattern
of development, offering fewer traditional amenities,
necessarily brings with it a correspondingly lower
level of investment in local public goods. The diffuse
automobile-oriented layout of most edge cities typically requires enormous public investment in roads as
well as water and sewer utilities. And despite the suc-

To be sure, Edge City is at least partly excused for
any shortcomings by Garreau's disclaimer, "I am a reporter, not a social critic." The book provides a finely
detailed portrait of an important and often misunderstood change in the way that U.S. urban areas are organized. T h e p h e n o m e n o n of edge cities certainly
deserves more attention from the mainstream of the
economics profession, not to mention other would-be
social critics. It may be the case, as Garreau's more
optimistic passages seem to imply, that edge cities represent a step toward a better form of social organization. Or edge cities may represent a futile attempt at
"city living with country taxes." Certainly this issue
bears a closer look.

Notes
1. In addition to focusing on his main argument, Garreau also
considers the effects of the production side of the economy,
explaining how recent changes in transportation and communication technology have accelerated the movement to edge
cities. The technological innovations of the past twenty years
(computer networks, fax machines, and the like) have clearly

56
Economic Review


contributed to the attractiveness of edge cities vis-a-vis traditional downtowns. Again, this rather obvious development
has generally received short shrift in analyses of the "new
suburbs."
2. Charles M. Tiebout, "A Pure Theory of Local Expenditures,"
Journal of Political Economy 64 (October 1956): 416-24.

. M a y / J u n e 1992

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