The full text on this page is automatically extracted from the file linked above and may contain errors and inconsistencies.
™?|Econoniic
lisaiS Review
FEDERAL RESERVE BANK O F ATLANTA
MARCH/APRIL 1991
Supply Shocks and Household
Demand for Motor Fuel
Beyond Plain Vanilla:
A Taxonomy of Swaps
FYI: The Impact of Private-Sector
Defense Cuts on Regions of the
United States
Book Review
The Interstate Banking Revolution:
Benefits, Risks, and Tradeoffs for Bankers and Consumers
by Peter S. Rose
Economic
Review
President
Robert P. Forrestal
Senior Vice President and
Director of Research
Sheila L. Tschinkel
Vice President and
Associate Director of Research
B. Frank King
Vice Presidents
William Curt Hunter, Basic Research
Mary Susan Rosenbaum, Macropolicy
Research Officers
William Roberds, Macropolicy
Gene D. Sullivan, Regional
Larry D. Wall, Financial
David D. Whitehead, Regional
Public Affairs Officer
Bobbie H. McCrackin
Publications
Joycelyn T. Woolfolk, Publications Coordinator
I.ynn H. Foley, Production
Carole Starkey, Graphics
Ellen Arth, Circulation
The Economic Review seeks to inform the public
about Federal Reserve policies and the e c o n o m i c
environment and, in particular, to narrow the g a p
between specialists and concerned laypersons
Views expressed in the Economic Review are not
n e c e s s a r i l y t h o s e of t h i s Bank or of the Federal
Reserve System.
Materia] may be reprinted or a b s t r a c t e d if the
Review and author are credited. Please provide the
Bank's Public Affairs Department with a copy of any
publication containing reprinted material
Free subscriptions and limited additional copies
are a v a i l a b l e from the Public Affairs Department,
Federal Reserve Bank of Atlanta, 104 Marietta Street,
N.W., Atlanta, Georgia 30303-2713 (404/521-8020)
Change-of-address notices and subscription canc e l l a t i o n s s h o u l d be s e n t d i r e c t l y t o t h e P u b l i c
Affairs Department. Please include the current mailing label as well as any new information.
ISSN 0732-1813
VOLUME 76, NO. 2, MARCH/APRIL 1991, ECONOMIC REVIEW
Supply Shocks and Household
Demand for Motor Fuel
W i l l i a m C. H u n t e r a n d Mary S. R o s e n b a u m
\2
Beyond Plain Vanilla:
A Taxonomy of Swaps
Research into the response of U.S. household
demand for motor fuel to oil price shocks during
the 1970-89 period lends perspective to the recent oil shock.
The author surveys numerous varieties of interest rate, currency, commodity, and equity swaps.
Peter A. A b k e n
30
R Y L
David D. W h i t e h e a d
42
Book Review
A r u n a Srinivasan
FEDERAL RESERVE BANK O F ATLANTA
The Impact of Private-Sector Defense Cuts on
Regions of the United States
The Interstate Banking Revolution:
Benefits, Risks, and Tradeoffs for Bankers and
Consumers
by Peter S. Rose
Supply Shocks and Household
Demand for Motor Fuel
William C. Hunter and Mary S. Rosenbaum
Many economists believe that oil price shocks to the U.S. economy cause changes in demand for oil that persist long after the shocks'first effects. Casual observation suggests that consumption of motor fuel during the past two decades has
not been very sensitive to motor fuel pnces. The authors' study of U.S. household demand for motor fuel from 1970
through 1989 supports an asymmetric response hypothesis, which holds that decreased demand for motorfuel immediately following an increase in its price will exceed the increased demand following a comparable price decrease. They
find no support for an explanation that links household demand to conservation policies.
T
he unexpected reduction in the world
supply of crude o i l — a n d subsequent
increase in its price—following the August 2, 1990, Iraqi invasion of Kuwait is
an example of what economists call a supply shock.
The term is used to refer to a situation in which
the supply of a key input into the economy's aggregate p r o d u c t i o n f u n c t i o n is u n e x p e c t e d l y
c h a n g e d (interrupted or s u p p l e m e n t e d ) or in
which the price of a key input changes substantially and quickly. Such shocks can affect the economy in numerous ways, leading to a number of
potential economywide adjustments. The scope of
these adjustments will depend on the nature and
size of the shock and on the economy's current
structure.
Stated differently, a supply shock is a change
in the economy's ability to produce a given level
of output at a given price. A favorable supply
shock, such as an increase in labor productivity
or a technological breakthrough, raises the level
of output produced by a fixed amount of input—
that is, for any given price, more can be prod u c e d . A n adverse s u p p l y s h o c k , such as an
increase in oil prices, lowers the output potential
for existing resources. Capital, because it becomes more expensive to operate, and labor, because each unit of labor has, in essence, less
capital with which to produce output, are both
less productive. At any price, less can be produced
with given inputs. For example, if a factory's fuel
bill that had been $100 per unit of output increases
to $125 per unit of output because of the rise in oil
prices, the production ability of both the existing
capital (plant and equipment) and labor are reduced.
FEDERAL RESERVE BANK OF ATLANTA
Adverse supply shocks like the infamous oil and
food price shocks of the 1970s can thus be thought
of as destroying some of the economy's existing
capital stock or as reducing labor productivity. Either outcome leads to decreases in equilibrium real
wages. The quadrupling of oil prices during the
supply shock o f 1974 (see Chart 1) provides a
good illustration of these points. In response to the
oil shock, m a n y firms scrapped m u c h of their
energy-inefficient plant and equipment. Supported
by a smaller capital stock with which to work, labor productivity naturally fell in the short run.
Economists have long speculated that certain
shocks, especially adverse supply shocks, can lead
to changes in behavioral relationships that persist
long after a shock's initial impulse has passed. The
U.S. economy has experienced several such shocks
in the last twenty years, and these episodes provide data that can help determine how households
and businesses respond. Some understanding of
ways the economy has adjusted in the past may
lend perspective on the recent oil shock and the
likely efficacy of policies designed to offset its impact. An examination of U.S. household demand
for motor fuel over the 1970-89 period, presented
in this article, sheds some light on these issues of
different sectoral responses to oil price shocks.
The authors are, respectively, vice president and senior financial economist responsible for basic research and vice president and senior economist in charge of the macropolicy
section of the Atlanta Fed's research department. They thank
Mary Beth Walker for helpful comments. Excellent research assistance was provided by Jeff Watson and Danny Moses. Mark
Rogers derived and calculated the motorfuel price index.
1
Chart 1
Oil Prices, 1968-90*
40
* Annual
average
crude oil refiners'
acquisition
cost,
composite.
Source: U.S. Department of Energy.
Sensitivity of Oil Consumption
to Oil Prices
The ease or difficulty with which the economy responds to a supply shock depends on the nature of
the commodity whose price changes. If there are
few acceptable substitutes for the commodity, as for
oil, then households and businesses find it difficult
to switch to an alternative in the short run. In this
circumstance, demand does not appear to be price
sensitive; it does not have much price elasticity (to
use economists' term for describing and measuring
the sensitivity of demand to price changes). In the
longer run, as substitutes for the commodity are developed or discovered, demand becomes more sensitive to price changes. In other words, the short-run
price elasticity of demand is less than the longer-run
price elasticity.
The oil price shocks of the 1970s were large and
disruptive. The first shock, between 1973 and 1974,
sent oil prices from about $3-60 per barrel (1972 average) to more than $10 per barrel in 1974.1 Moreover, this episode included an embargo limiting U.S.
2
gasoline supplies and resulting temporarily in informal rationing and other nonprice restraints on gasoline purchases. The second shock, a series of price
increases during 1979 and 1980, raised the per barrel
cost from $12.46 in 1978 to more than $35.00 in
1981.
Despite much early empirical evidence to the
contrary, recent history lends casual support to the
notion that U.S. oil consumption has not been very
sensitive to oil prices, especially since 1975.2 As
Stephen P.A. Brown and Keith R. Phillips (1989a)
have noted, U.S. c o n s u m p t i o n of oil increased
sharply between 1975 and 1979, despite the quadrupling of oil prices following the 1974 oil shock. Furthermore, although both oil prices and consumption
fell from 1981 through 1985, consumption increased
only modestly after prices plunged in 1986. Each of
these observations is consistent with the assumption
that the short-run price elasticity of demand for oil is
quite low.
Brown and Phillips observed that at least three
theories compete to explain the apparent insensitivity of oil consumption to oil prices. The "nonprice
conservation" theory is based on the notion that
ECONOMIC REVIEW, MARCH/APRIL 1991
changes in U.S. government policies reduced the
growth in demand for oil independently of changes
in the price of oil. For example, the Energy Policy
and Conservation Act of 1975 and the National Energy Act of 1977, which mandated a number of conservation measures, imposed m i n i m u m average
gas-mileage standards for U.S. auto manufacturers
and a 55-mile-per-hour national speed limit, as well
as improvements in technology. A second theory is
that U.S. oil consumption responds asymmetrically to
changes in oil prices, falling more following a price
rise than it rises after an oil price decline.
Neither the nonprice conservation or asymmetric
response theory stood up to empirical testing at the
aggregate ( e c o n o m y w i d e ) level by Brown and
Phillips (1989a). Using a quarterly econometric model of U.S. oil consumption applied to the period covering the first quarter of 1972 through the first
quarter of 1988, the authors rejected both theories.
A third theoretical explanation of the observed insensitivity of U.S. oil consumption to changes in oil
prices is based on the notion that oil consumption
patterns are persistent. According to this perspective,
because substantial changes in the economywide ratio of oil consumption to output require new capital
investment, consumption responds very slowly to oil
price changes, giving the possibly false impression
that oil consumption is not very sensitive to price.
This observation is simply another way of saying that
the long-run price elasticity of demand for oil is
more than the short-run elasticity. Empirical support
demonstrating the lag in the responsiveness of oil
consumption to price changes appears in studies by
W.W. Hogan (1989), Dermot Gately and Peter Rappoport (1988), and Brown and Phillips (1984).
Another explanation, consistent with the consumption persistence theory, is that the household
and business sectors of the U.S. economy have different sensitivities to oil shocks and different time
patterns of adjustment to changes in oil prices. For
example, businesses, especially manufacturing and
transportation, may face very high fixed costs of
converting to alternative energy sources, or they
may have extremely limited opportunities to conserve. For such producers to decrease oil dependency may require investment in more fuel-efficient
plant and equipment, so reducing demand might
be difficult in the short run. At the same time,
households may have more discretion in their conservation o p t i o n s because conservation at the
household level involves trading off comfort (heat,
air conditioning, private car use) for cost. Thus, the
sensitivity of household motor fuel consumption to
changes in fuel prices may differ significantly from
that of aggregate or economywide oil consumption
FEDERAL RESERVE BANK OF ATLANTA
to changes in oil prices. Given these considerations, it is possible that broadly defined energy
conservation policies (not targeted to business or
household behavior) will fail to elicit the expected
response.
The specific question investigated is whether the
adverse oil shocks of 1974 and 1979 led to significant changes in household motor fuel consumption
patterns. Providing answers to this question as well
as empirical evidence on the nonprice conservation
and asymmetric response theories at the level of the
household should prove valuable in any attempt to
assess the impact of the 1990 oil shock on household demand for gasoline during the next several
years. The same evidence could be useful in the design of energy conservation programs and contribute
to the formation of future tax (fiscal) policy.
The research published here is a first step toward
understanding the various ways sectors respond to
oil price shocks. In the study a simple quarterly
econometric model of household motor fuel demand has been used to conduct tests of the nonprice c o n s e r v a t i o n a n d asymmetric response
theories for household motor fuel consumption. The
analysis was carried out using the linear expenditure
system derived by Richard Stone (1954). A brief intuitive explanation of this approach to demand analysis appears in the next section. Readers interested
in a rigorous derivation of the linear expenditure
system from first principles are referred to the box
on page 4.
Household Demand: The Linear
Expenditure System Defined
The demand function of an individual or household for a product is simply a schedule of the
amounts of the product the individual or household
would buy at various possible prices in a particular
period for a given level of income. Thus, the concept of a demand function describes a functional relationship between two variables: the price of a
product and the quantity of the product demanded,
holding income constant. However, it is generally
true that the demand for any given product will also
depend on a host of considerations or influences besides price.
Depending on the issues being examined, various of these other influences—which include the
prices of other goods or services (in particular, possible substitutes), the household's income and
tastes, and expected future prices—should be taken
into account explicitly in the household's demand
3
Deriving the Linear Expenditure System
Utility Maximization and Demand Functions
The classical consumer or household demand model
is based on the assumption that the household chooses
to consume that set of goods which yields the household the maximum utility or satisfaction. This choice is
constrained by the size of the household's income. The
total utility the household derives from the consumption of a set of goods can be represented by a utility
function. In general notation, the household's utility
function can be written as
U- Utqv q2,...,
qn\
second-order conditions for a maximum—that is, that
the matrix of second-order partial derivatives (the Hessian matrix) is negative definite and symmetric—are assumed to hold. The solution of the n equations in
relationship (B5) and the budget constraint in equation
(B3) give the system of household demand equations.
Depending on the exact functional form of the household's utility function, the demand equations may be
written explicitly as
qr
q^pv
. . . , pn, EX
(B6)
(Bl)
The Linear Expenditure System
where U is household utility and qv . . . , qn are the
quantities of the n different (exhaustive) goods consumed by the household. It is assumed that the
household's utility function is twice differentiable
with respect to each of the goods contained in the
function. In other words, the changes in utility associated with changes in the amounts of each good consumed can be computed. It is further assumed that
marginal utility of each good (the extra utility or satisfaction derived from one additional unit of any one
of the goods holding constant the levels of all other
goods) is positive.
The household's budget constraint can be written as
n
S M=E>
i= 1
(B2)
where the p(s are prices, the qfs are quantities, and E
represents total household expenditures or income.
For ease of presentation, boldface type denotes vectors, the entire array of prices and quantities. Using
this notation equation (B2) can be rewritten compactly as
p'q = E,
(B4)
where X is the Lagrange multiplier. The first-order
conditions for the maximization of equation (B4)
are
dU/dq = \p,
(B5)
along with the budget constraint given in equation
(B3)- This solution is a global maximum because the
4
n
U - X ^ r t f ^
i— 1
(B7)
where qi > qt° and q? is the minimum amount or
subsistence level of the ith good that is consumed.1
If this particular functional form of the household's
utility function is substituted into the Lagrangian
equation (B4), the first-order conditions for utility
maximization are
n
ft X (<7, - qpPj Vtq{ - qp = xp,.,
J- 1
(B8)
which yield demand curves (expenditure functions) of
the following form:
(B3)
where the prime denotes vector transposition. Using
the differentiable calculus, the household's utility maximization problem can be expressed in terms of the Lagrangian function
U(q)-Kp'q-E\
The Linear Expenditure System was first proposed and estimated by Richard Stone (1954) and
represents the first formal treatment of demand analysis using a specific utility function. That utility function is
n
M r
e
r Pi tf+J^O?- 2 Pjip*
j- i
i= 1,..., n.
CB9)
The demand or linear expenditure system given in
equation (B9) is estimated subject to the technical restriction that the /6?s be normalized so that they sum to
unity and that 0 < /3(- < 1 for each of the equations. The
jSj-s represent the marginal budget shares of the n
goods. Because the demand equations have been derived from a specific utility function, they automatically
satisfy the restrictions imposed by neoclassical demand
theory.2
The minimum or subsistence quantities of the
goods in equation (B9) are in general unknown and
must be estimated. If 7}i is defined as the subsistence
ECONOMIC REVIEW, »MARCH/APRIL 1991
level of the ith good consumed by the household, the
equation system (B9) can be written in a form
amenable to empirical estimation. The estimable system is written as
i = ViPi + P, (E-2 ViPj) + uit i= 1,. . •, » , (BIO)
J" 1
where the u.s are disturbance terms.
e
Notes
1. The linear expenditure system can also be derived
from a host of other more complicated utility functions, all with their own particular advantages. For
examples of these approaches see Klein and Rubin
(1947-48), Frisch (1959), Houthakker (I960), Parks
(1969), Christensen, Jorgenson, and Lau (1975), and
Berndt, Darrough, and Diewert (1977).
function. Household demand for motor fuel certainly seems based on factors other than price. In the
analysis that follows, household demand for motor
fuel is modeled as a function of the price of motor
fuel, household income, and the prices of other
goods and services. Although simple in form, this
demand function is in fact very general and is consistent with the standard consumer utility maximization framework of contemporary microeconomic
theory.
Household demand functions can be easily transformed into expenditure functions, which represent
total household expenditure on a given good as determined by the price of the good in question,
household income, and the prices of all other goods
that elicit household consumption expenditures. Because these expenditure functions are simple transformations of household demand functions, they
share all of the theoretical properties underlying the
demand functions derivable from budget-constrained
household utility maximization (see the box). 3
The form of the household motor fuel demand or
expenditure function used in the empirical analysis
reported here can be written as
n
e
m
=
-nmPm
+
VP
+ U
m'
(1)
2. These conditions include Engel and Cournot aggregation, homogeneity of degree zero in prices and total expenditure, and a symmetric substitution matrix.
The restriction that the /3( be bounded by zero and
unity means that the substitution matrix will also be
negative semidefinite as required by standard demand theory.
reflects any errors associated with fitting the function
to actual data.
Expenditure or demand functions of this type,
which have been widely used, have an intuitive interpretation. In terms of total expenditures, this representation assumes that the h o u s e h o l d first
purchases a minimum required (that is, nondiscretionary) quantity o f each commodity, then distributes its remaining income over all commodities
in fixed proportions. Thus, the household's total income can be decomposed into a subsistence component (the income spent on the minimum required
quantities of the commodities) and a supernumerary
component (the remaining income spent on all of
the commodities). Specialized to the case of motor
fuel in equation (1) above, the household's minimum required purchase (subsistence quantity) of
motor fuel is represented by the parameter r]m,
which is estimated statistically. At the current market
price this subsistence quantity of motor fuel costs the
household the amount pmVm• The proportion of its
supernumerary income (total income minus the total cost of the minimum required amounts of the
other goods) spent on motor fuel is given by parameter f3m. This parameter is estimated statistically
along with the 17j parameters appearing in the expenditure function.
7-1
(See the box.) As stated earlier, in this formulation the household's total expenditure on motor
fuel in a given period, em, is expressed as a function of the price of motor fuel, pm\ the household's total income, E\ and the prices of all other
goods consumed by the household, the p j terms.
The terms denoted by 17 m, f3m, and -q- are parameters to be estimated statistically. The term denoted by um is a r a n d o m d i s t u r b a n c e term that
FEDERAL RESERVE BANK OF ATLANTA
Properties of the Demand Function
Examining the sensitivity of motor fuel demand
to changes in household income and the price of
motor fuel gives insight into the behavior of household motor fuel consumption patterns over time.
The sensitivity of motor fuel demand to changes in
household income is readily obtained by computing
5
the household's income elasticity-of-demand index
for motor fuel. This index measures the relationship
between a relative change in income and the consequent relative change in motor fuel demand, other
things being constant. The income-elasticity index,
which will be denoted by r m , can be computed using the formula
In this formula, w m is the proportion of the household's total income spent on motor fuel—that is, w m
= pmqm/E,
where qm is the total quantity of motor
fuel purchased, and (3m is the proportionality parameter discussed above. Economic theory requires that
the parameter /3m be nonnegative (0 < /3m < 1).
Thus, the income-elasticity index for motor fuel is
positive, implying that motor fuel is a normal good.
Normal goods are those for which demand increases as income increases. Hence, household demand
for motor fuel should increase as household income
increases, other things being held constant.
Own-price elasticity of demand is generally defined as the response of quantity demanded to a given percentage change in the price of a particular
good. The own-price elasticity-of-demand index for
motor fuel, a m , can be computed using the following formula:
am--l+a-pmXv
JqJ-
C3)
The own-price elasticity-of-demand index measures
the proportional magnitude that quantity demanded
changes as price changes. With (0 < (3 m < 1) and
(qm - r] m > 0), it follows that the own-price elasticity
index is negative, implying that an increase in the
price of motor fuel reduces the quantity demanded.
Household Demand for Motor Fuel,
1970-89
The empirical analysis discussed here was carried
out by estimating the demand relationship given in
equation (1) using quarterly data on U.S. household
motor fuel expenditures during the period 1970-89Total quarterly household expenditures on motor fuel, em, were taken from national income and product
accounts as a component of personal consumption
as estimated by the Bureau of Economic Analysis
(BEA) of the U.S. Department of Commerce. The
price of motor fuel, pm, is the consumer price index
(CPI) component for the series as estimated by the
Bureau of Labor Statistics (BLS), U.S. Department of
6
Labor. Total disposable household income, E, is defined as personal income in the United States (less
taxes) and is taken from the national income and
product accounts as estimated by the BEA. The
prices of all other goods consumed by the household are measured using the CPI minus the motor
fuel component. This index—based on the overall
CPI and the motor fuel component—is derived using
the methodology explained in Chester V. McKenzie
(1961). The index was calculated for each year separately to constrain changes in relative importance
by k n o w n relative share figures released by the
BLS. Each series was then linked to the other with
1982-84 having been set as the base period equal to
100. Using this price index, pj, equation (1) can be
rewritten in final form as
e
m=
V
m
P
m
+
i 3
m
( E - V
m
P
m
- V
I
P
i
)
+
um.
(4)
This household motor fuel demand function is
nonlinear in its parameters and thus must be estimated using a nonlinear estimation technique. Equation
(4) has been estimated by standard maximum likelihood techniques using the Davidson-Fletcher-Powell
algorithm (see A. Ronald Gallant 1990) with an adjustment for the presence of first-order serial correlation of the residuals. Serial correlation occurs when
the errors associated with fitting the expenditure
function to the data from one period (quarter) carry
over into future periods (quarters). First-order serial
correlation means that the errors from one quarter
are correlated or related to the errors in the ensuing
quarter. The presence of this serial correlation detracts from the efficiency of the statistical estimation,
making estimated parameter values seem more precise than they truly are. A statistical procedure that
corrects for this potential problem has been employed. The parameter values resulting from the estimation are given in Table 1.
As shown in Table 1, the key estimated coefficients are statistically significant, being well in excess
of their standard errors. This fact indicates that these
parameters can be used with confidence in discussing household motor fuel demand relationships
during the period of analysis. These parameter estimates also are consistent with underlying economic
theory in that they satisfy the qualitative restrictions
implied by standard behavioral assumptions and
model structure. That is, in line with the discussion in
the previous section, the m i n i m u m (subsistence)
quantities of motor fuel, measured by r) m , and the index or composite commodity, measured by r\j, are
positive, and the supernumerary or marginal-budgetshare parameter,
measuring the proportion of supernumerary income spent on motor fuel, is positive
ECONOMIC REVIEW, »MARCH/APRIL 1991
e
m=7lmPm+
Table 1
Estimated Demand (Expenditure) Function
Coefficients for U.S. Household
Motor Fuel, 1979-80
Parameter
Coefficient
Standard Error
t- value
T] m
.560
.032
17.50*
ßm
.013
.001
13.00*
ri I
1.037
.620
1.67
* Statistically significant at the 1 percent level or
higher.
and less than unity, indicating that the household's
marginal utility for motor fuel consumption is decreasing.
Nonprice Conservation Theory
The nonprice conservation theory of oil consumption's insensitivity to oil prices is based on the notion
that national energy conservation efforts following
the oil price shock of 1974 should have reduced the
economy's dependence on foreign oil. These policies included imposing fuel mileage standards for
U.S. automobile manufacturers, excise taxes on "gas
guzzlers," and special tax incentives for producing
alternatives to fossil fuels.
As noted earlier, Brown and Phillips rejected the
nonprice conservation theory at the aggregate level.
As a way of providing evidence on these conservation
measures' effectiveness at the household level, the basic model was tested for the presence of a significant
(negative) linear technological or conservationrelated trend in household motor fuel consumption
expenditures during the sample period. A statistically
significant trend in household motor fuel consumption would suggest that something other than oil
prices, income, and prices of other goods was affecting the demand for motor fuel. Testing the model for
this trend in consumption expenditures involved estimating equation (4) in the following form:
FEDERAL RESERVE BANK OF ATLANTA
ßm^E^m
PnT
P/)
(5)
where t is a simple time trend variable. Because
this time variable captures most systematic influences on demand other than mandated changes, a
significant coefficient on the trend variable can be
interpreted as consistent with the nonprice conservation theory.
If the energy conservation measures were effective, the coefficient 0m on the time trend variable
should be negative and statistically significant, supporting the nonprice conservation theory. The estimated value of this time trend coefficient was 0.31,
with standard error of 0.23 and a statistically insignificant t-value of 1.35. The values of the other
parameters were not significantly different from
those given in Table 1. Thus, there was not any statistically significant general d o w n w a r d drift in
household motor fuel consumption expenditures
during the sample period. 4 O n the basis of this evidence, it seems clear that if conservation measures
were at all effective they were effective only in particular years following shocks, not throughout the
entire sample period. This finding of very little support for the systematic effectiveness of nonprice
conservation measures at the level of the household
during the 1970-89 period seems to agree with casual observation and is consistent with the findings reported by Brown and Phillips for aggregate U.S. oil
consumption.
It should be noted that asymmetries in the responsiveness of household motor fuel expenditures
to price changes may also explain why the nonprice conservation theory does not seem to have
applied during the whole sample period (1970-89).
This period included two episodes of price declines
in addition to the two adverse shocks. The mixed
pattern of price changes during the period, combined with a possible asymmetric household demand response, contributes to the difficulty in
assessing the long-term effectiveness of U.S. energy
conservation measures.
Asymmetric Response Theory
High frequency (monthly and daily) motor fuel
price data for the 1970s and 1980s reveal that price
increases were sudden while declines tended to be
more gradual. Because tests used in the research reported on here are based on quarterly data, they
cannot distinguish different price change profiles
7
from more high frequency price series. Thus, the
tests of the asymmetric response theory described in
this section distinguish price changes only by direction, not speed or persistence.
To test for possible asymmetries in the responsiveness of household motor fuel expenditures to
changes in the price of motor fuel—that is, that demand responds differently to price increases than to
price decreases—a series of statistical tests on the
equality of the motor fuel expenditure (demand)
equations across subperiods was conducted. Four
subperiods were examined. The results of the statistical tests of equality of the expenditure (demand) functions across these subperiods appear in
Table 2.
The first subperiod—the base period—begins
with the first quarter of 1970 (70:1) and runs through
Table 2
Tests of Equality of Motor Fuel Expenditure
Functions during Periods of Adverse (Rising),
Stable, and Favorable (Falling)
Motor Fuel Prices*
Period
Price Trend
1970:1-1973:4
vs.
1974:1-1978:4
Stable
1970:1-1973:4
vs.
1979:1-1985:4
Stable
1970:1-1973:4
vs.
1986:1-1989:4
Stable
1974:1-1978:4
vs.
1986:1-1989:4
Adverse
1979:1-1985:4
vs.
1986:1-1989:4
Adverse
Test Result*
Reject
Adverse
Reject
Adverse
Accept
Favorable
Reject
Favorable
Accept
Favorable
* Likelihood ratio test of equality of expenditure functions at 5 percent level.
8
the end of the fourth quarter of 1973 (73:4). It
represents a regime of fairly stable motor fuel and
oil prices. The second subperiod covers 74:1-78:4,
and the third encompasses 79:1-85:4. Both of
these subperiods were dominated by sharp increases in motor fuel prices at the beginning of
the period as a result of the 1974 and 1979 adverse oil shocks. The fourth subperiod, 86:1-89:4,
was characterized by sharply declining motor fuel
and oil prices.
Note that prices did not rise steadily throughout
either of the periods designated as having adverse
oil price trends. Each adverse trend period has
been designated to extend from the beginning of
one shock to either the next adverse shock or a
subsequent dramatic change in the direction of
prices. This delineation allows including the response time as part of the period being considered and therefore is consistent with the theories
being tested. In this way, the period from 74:1 to
78:4 is deemed an adverse price trend episode
even though prices did not rise uniformly over the
period. So is the entire 79:1-85:4 period, even
though prices declined somewhat at the end of
that time. According to this treatment, the economy experienced two consecutive adverse price
shocks.
Unlike the aggregate demand for oil (see Brown
and Phillips 1989a, b), household demand for motor
fuel does not appear to behave symmetrically during
periods of increasing and decreasing motor fuel
prices. This conclusion is evidenced in part by the
test results presented in Table 2, where the equality
of the 70:1-73:4 subperiod expenditure (demand)
function with all other subperiod expenditure functions except the 86:1-89:4 subperiod has been rejected. Further evidence derives from the fact that the
expenditure function for the period exhibiting the
most adverse, or sharply rising, prices (74:1-78:4) is
significantly different from the subperiod during
which prices fell sharply (86:1-89:4). No significant difference was found between the 70:1-73:4
base period, characterized by stable motor fuel
prices, and the period of sharply falling motor fuel
prices.
Although the tests recorded in Table 2 indicate
that the household motor fuel expenditure (demand) function is not symmetric around motor fuel
price increases and decreases, these tests do not
shed light on the economic implications of the
asymmetric responses. In the next section of this article these economic implications are explored by
examining the nature of the income and price elasticities implied by the subperiod expenditure (demand) functions.
ECONOMIC REVIEW, »MARCH/APRIL 1991
Income Elasticities of Demand for
Motor Fuel
The household income-elasticity index can be
computed using the formula given in equation (2).
This index measures the relationship between a relative change in household income and the consequent relative change in demand for motor fuel,
other things constant. As noted earlier, income elasticities are positive for normal goods—that is, dem a n d increases as income increases, other
conditions remaining constant.
Household income elasticities of demand for motor fuel for each of the subperiods examined in
Table 2 are given in Table 3- These income elasticities were computed using equation (2) with the subperiod parameter estimates and the mean values of
the other relevant variables for each subperiod.
As can be seen in Table 3, all subperiod income
elasticities are positive (motor fuel is a normal good),
ranging from a high of 1.10 for the 70:1-73:4 base
period to a low of 0.34 for the 79:1-85:4 subperiod.
The estimated elasticity index of 1.10 in the 70:1-73:4
base subperiod implies that households treated gasoline as a luxury good during this period. A good is
Table 3
Household Income Elasticities of
Demand for Motor Fuel
Income
Period
Price Trend
Elasticity ( r m )
1970:1-1973:4
Stable
1.10
1974:1-1978:4
Adverse
0.58
1979:1-1985:4
Adverse
0.34
1986:1-1989:4
Favorable
0.74
1970:1-1989:4
FEDERAL RESERVE BANK O F ATLANTA
0.47
considered a luxury good if its income elasticity of
demand exceeds unity. That is, for a given percentage increase in the household's income, the demand
for the luxury good increases by a more than proportionate amount, other things being equal.
Following the 1974 oil shock, all subperiod income elasticities are estimated to be below unity.
Thus, it appears that the first oil shock in effect converted gasoline from a luxury good into a necessity.
A good is considered a necessity if it is normal with
an income elasticity less than unity. The estimated
income elasticities dropped dramatically relative to
the base-period value during both oil-shock subperiods. These index values suggest that the high price
of gasoline, combined with energy conservation
measures such as car pooling and improved fuel efficiency of automobiles, may have served to reduce
household dependence on motor fuel during these
particular subperiods. This idea seems particularly
plausible given the time required for these measures
to have taken effect and exerted an impact on demand. Because oil and oil products have few close
substitutes, it is reasonable to expect income elasticities to diminish as price elasticities increase over
the longer run, when alternatives are developed and
new habits are solidified.
The income-elasticity index increased from a low
of 0.34 during the subperiod of the second adverse
oil shock to a value of 0.74 during the 86:1-89:4 subperiod, which was characterized by the positive oil
shock and falling oil and motor fuel prices. This
change is somewhat disturbing because it suggests
that reversal of the conservation-related gains following the 1974 and 1979 shocks may have begun during the later subperiod. The rebound in income
elasticity implies that the oil price declines of 1986:1
through 1989:4 were seen as permanent. The fixed
costs of conservation and conversion were not expected to be incurred again, and the change in behavior was abandoned. The lower relative price of
motor fuel may have moved it back toward the
luxury-good category.
Price Elasticity of Demand for
Motor Fuel
In the research discussed here price elasticities
of demand for motor fuel have been computed
using the formula given in equation (3). The priceelasticity-of-demand index measures the proportional magnitude that quantity demanded increases as
price falls. Because motor fuel is a normal good, the
price-elasticity index should be negative, indicating
9
that demand for motor fuel is inversely related to the
price of motor fuel. The price elasticities of demand
for each of the four subperiods examined above are
given in Table 4.
The estimated price elasticities for each of the
subperiods and the entire sample period have the
anticipated negative sign. The results in Table 4 corroborate those reported in Table 3. For the preshock
base subperiod (70:1-73:4) household motor fuel demand was very inelastic or insensitive to the price of
motor fuel. However, following the first oil shock in
1974, the sensitivity of the household motor fuel demand function increased noticeably. The index more
than doubled in absolute value, increasing from
-0.40 during the preshock base subperiod to a value
of -0.85 during the subperiod of the first oil shock.
On the other hand, the estimated demand elasticity
for the 86:1-89:4 subperiod (characterized by dramatic declines in oil and motor fuel prices) was
again approaching the value estimated for the base
preshock subperiod.
This pattern of response in household motor fuel
demand to rising and falling gasoline prices lends additional support to the asymmetric price response theory. As can be seen in Table 4, the drop in demand
resulting from the motor fuel price increase following
the 1974 adverse oil shock exceeds the increase in demand resulting from the lower motor fuel prices that
followed the favorable 1986 oil price shock. 5 In ad-
Table 4
Price Elasticities of Demand for Motor Fuel
Price
Period
Price Trend
Elasticity (a m )
1970:1-1973:4
Stable
-0.40
1974:1-1978:4
Adverse
-0.85
1979:1-1985:4
Adverse
-0.63
1986:1-1989:4
Favorable
-0.47
1970:1-1989:4
10
-0.61
dition, the trend toward a more inelastic household
motor fuel demand function since the 1974 subperiod is consistent with the notion that the energy conservation measures introduced following the 1974
adverse oil shock had lost much of their effectiveness by the early 1980s.
However, these same results also are consistent
with the idea that conservation measures and the development of alternatives have limitations. That is, as
prices rise, equal marginal increases in oil prices do
not yield equal marginal declines in consumption.
The initial price increases elicit conserving behavior
and a search for substitutes. Additional marginal conservation efforts yield smaller returns, though, so
that, within some limited period of time, additional
price increases result in decreasing adjustments to
motor fuel demand.
Implications and Conclusions
The widespread belief among economists that adverse supply shocks lead to changes in behavioral
relationships that persist long after a shock's initial
impulse has passed is examined in this article. In
particular, the question of whether U.S. household
motor fuel demand is sensitive to the price of motor
fuel is investigated. Casual observation of household
gas and oil consumption during the last two decades
would suggest that household motor fuel consumption is not very sensitive to motor fuel prices. Two
popular theories have been advanced to explain this
nonsensitivity—the nonprice conservation theory
and the asymmetric response theory.
At the household level during the 1970-89 period,
the empirical results reported in this article do not
support the nonprice conservation theory—which
holds that household demand for motor fuel should
have become less sensitive to changes in motor fuel
prices since the 1974 oil shock as a result of gasoline and energy conservation policies. The differing
price and income elasticities associated with various
oil price trends support the asymmetric response
theory, which hypothesizes that the decrease in demand for motor fuel subsequent to an increase in its
price will exceed, in percentage terms, the increase
in demand following a comparable decrease in the
price of motor fuel. For the time periods covered by
the analysis discussed here, the estimates from the
econometric model reveal that the change in price
elasticity as prices rise is greater than the change as
prices fall. Future research efforts will be directed
toward investigating this asymmetry and strengthening the basis for elasticity forecasts to allow for esti-
E C O N O M I C REVIEW, »MARCH/APRIL 1991
mates of d e m a n d
response to price changes
not o n l y direction but also different speeds
of
c o n s u m e r reaction to the price increase will d e p e n d
and
o n w h e t h e r the price increase is v i e w e d as permanent or temporary.
varying persistence.
The test results c o n c e r n i n g U.S. h o u s e h o l d m o t o r
T h e relatively inelastic d e m a n d for o i l suggests
fuel d e m a n d reported in this article suggest that if re-
that, at least in the short run, a m o t o r fuel (gasoline)
s p o n s e to the 1990 oil s h o c k follows previous pat-
tax is a g o o d source o f revenue, considering that the
terns, gasoline a n d oil d e m a n d g r o w t h will s l o w as
tax base ( m o t o r fuel c o n s u m p t i o n ) is n o t very re-
the price elasticity o f d e m a n d increases a n d the in-
sponsive to the tax rate. At the s a m e time, a n oil or
c o m e elasticity declines. These responses will proba-
gasoline excise tax is not likely to elicit c o n t i n u e d or
bly b e smaller t h a n those to earlier oil price shocks,
p e r m a n e n t conservation efforts unless the tax rate is
h o w e v e r , because the payoff for increasing conser-
increased o v e r t i m e , b e c a u s e the m a r g i n a l savings
vation a n d switching t o substitutes decreases for ev-
declines over time.
ery m a r g i n a l i n c r e a s e i n o i l p r i c e s . I n
addition,
Notes
1. This measure is the composite refiners' acquisition cost.
2. For a review of this evidence through 1980, see Bohi
(1981).
3. These demand functions are homogeneous of degree
zero in prices and income and satisfy the adding-up criterion, and the matrix of substitution terms is symmetric
and negative semidefinite.
4. However, it should be noted that, because the coefficients in Table 1 are estimated with a correction for the
possibility of serially correlated residuals, it is possible
that any technological drift in household motor fuel
consumption over the sample as a result of energy or
gasoline conservation measures was o f a nontrivial
(nonlinear) form captured by the time-series properties of the residuals of the model. The value of the
first-order auto correlation coefficient for equation (4)
was estimated to be 0.67 and is only marginally statistically significant.
5. Note that there was considerable nonprice rationing of
motor fuel coincident with price increases early in the
1974-78 period. This factor may introduce an upward
bias to the price elasticity measure for that period.
References
Berndt, Ernst, M.N. Darrough, and William E. Diewert.
"Flexible Functional Forms and Expenditure Distributions: An Application to Canadian Consumer Demand
Functions." University of British Columbia, Department
of Economics, Discussion Paper 77-10, 1977.
Bohi, D.R. Analyzing Demand Behavior: A Study of Energy
Elasticities. Baltimore, Md.: Johns Hopkins University
Press for Resources for the Future, 1981.
Brown, Stephen P.A., and Keith R. Phillips. "The Effects of
Oil Prices and Exchange Rates on World Oil Consumption." Federal Reserve Bank of Dallas Economic Review
(July 1984): 13-21.
. "An Econometric Analysis of U.S. Oil Demand."
Federal Reserve Bank of Dallas Working Paper No.
8901, January 1989a.
. "Oil Demand and Prices in the 1990s." Federal Reserve Bank of Dallas Economic Review (January 1989b):
1-8.
Christensen, Laurits R., Dale N. Jorgenson, and Lawrence J.
Lau. "Transcendental Logarithmic Utility Functions."
American Economic Review 65 ( J a n u a r Y 1975): 37-54.
Frisch, Ragnar A. "A Complete Scheme for Computing All
Direct and Cross Demand Elasticities in a Model with
Many Sectors." Econometrica 27 (April 1959): 177-96.
FEDERAL RESERVE BANK OF ATLANTA
Gallant, A. Ronald. Nonlinear
Statistical
York: John Wiley and Sons, 1990.
Models.
New
Gately, Dermot, and Peter Rappoport. "The Adjustment of
U.S. Oil Demand to the Price Increases of the 1970s."
The Energy Journal 9 (1988): 93-107.
Hogan, W.W. "A Dynamic Putty-Semi-Putty Model of Aggregate Energy Demand." Energy Economics 11 (1989):
53-69.
Houthakker, Hendrik S. "Additive Preferences." Econometrica 28 (April I960): 244-57.
Klein, Lawrence R., and Herman Rubin. "A Constant Utility
Index of the Cost of Living." Review of Economic Studies 15 (1947-48): 84-87.
McKenzie, Chester V. "Technical Notes: Relative Importance o f CPI C o m p o n e n t s . " Monthly Labor Review
(November 1961): 1233-36.
Parks, R.W. "Systems of Demand Equations: An Empirical
Comparison of Alternative Functional Forms." Econometrica 37 (October 1969): 629-50.
Stone, Richard. "Linear Expenditure Systems and Demand
Analysis: An Application to the Pattern of British Demand." Economic Journal 64 (September 1954): 511-27.
11
Beyond Plain Vanilla:
A Taxonomy of Swaps
Peter A. Abken
Since their introduction over a decade ago, swaps have become an important tool for financial risk management.
Generally, swaps alter the cash flows from assets or liabilities into preferred forms. Basic swaps have branched into
many variants, some more popular and successful than others, each geared toward meeting specific customer
needs in various markets. The author describes the features and typical applications of many variants of the four
basic swap types—interest rate, currency, commodity, and equity.
wap contracts of various kinds have become a mainstay of financial risk management since their introduction in the late
1970s. In the most general terms, a swap
is an exchange of cash flows between two parties,
referred to as counterparties in the parlance of swap
transactions. Swaps, which transform the cash flows
of the underlying assets or liabilities to which they
are related into a preferred form, have been used in
conjunction with positions in debt, currencies, commodities, and equity. Most swap agreements extend
from one to ten years, although many have been arranged for much longer periods.1
S
The key players responsible for originating and
propelling the swaps market are money center
banks and investment banks. These institutions benefit from the fee income generated by swaps, which
are off-balance-sheet items, and by the spreads that
arise in pricing swaps. Innovations in the swaps
market, as in other financial services areas, may be
characterized as a Darwinian struggle, in which
competition heats up and margins narrow as a particular kind of swap becomes accepted and widely
used. Such swaps are disparagingly said to be trad-
12
ed "like commodities." That is, little value is added
by the dealer in structuring a swap and bringing
counterparties together; consequently, little return is
realized for the service of intermediation or position
taking.
Perhaps the most basic, and most popular, swap
involves the conversion of interest payments based
on a floating rate of interest into payments based on
a fixed rate (or vice versa). Because many variants of
interest rate and other swaps have emerged over the
years, this most basic type has become known as the
"plain vanilla" swap. 2 As swap forms take on plain
vanilla status, the firms that originated them are compelled to develop new types of swaps to regain their
margins, amounting to m o n o p o l y rents, on new
products. Some swap variations succeed, while others languish or fail.
In this article the plain vanilla swap is a starting
point for a detailed taxonomy of the various species
and subspecies of swaps. Swap variants are classified along cladistic principles, categorized and compared in terms of their features and applications.
Examples illustrate many of the important types of
swaps.
ECONOMIC REVIEW, »MARCH/APRIL 1991
The Market
A Brief History. Before taking a detailed look at
swaps, an overview of the market will help put their
proliferation into perspective. Although some swaps
had been arranged in the late 1970s, the first major
transaction was a 1981 currency swap between IBM
and the World Bank. This deal received widespread
attention and stimulated others.
The currency swap actually evolved from a transaction popular in the 1970s, the parallel loan agreement, that produced cash flows identical to a swap's.
For example, in one of these agreements a firm in
the United States borrows a million dollars by selling
a coupon bond and exchanges (swaps) this amount
for an equivalent amount of deutsche marks with a
German firm, which borrows those deutsche marks
in its domestic market. This is the initial exchange of
principal. Thereafter, the U.S. firm makes markdenominated coupon payments and the German
firm makes dollar-denominated coupon payments.
Upon maturity of the underlying debt, the firms swap
principal payments. These firms have effectively borrowed in one another's capital markets, although for
a variety of reasons (such as foreign exchange controls or lack of credit standing in foreign markets)
they could not borrow directly. As Clifford W. Smith,
Charles W. Smithson, and Lee Macdonald Wakeman
(1990a) point out, the problems with such an agreement were that default by one firm does not relieve
the other of its contractual obligation to make payments and that the initial loans remain on-balancesheet items during the life of the agreement for
accounting and regulatory purposes. The currency
swap, on the other hand, stipulates that a default terminates the agreement for both counterparties and, in
general, limits credit-risk exposure to the net cash
flows between the counterparties, not the gross
amounts. This type of currency swap is essentially a
sequence of forward foreign exchange contracts.^
Following the 1981 currency swap, the first interest rate swap, in mid-1982, involved the Student
Loan Marketing Association (Sallie Mae). With an investment bank acting as intermediary, Sallie Mae issued intermediate-term fixed rate debt, which was
privately placed, and swapped the coupon payments
for floating rate payments indexed to the threemonth Treasury bill yield. Through the swap, Sallie
Mae achieved a better match of cash flows with its
shorter-term floating rate assets.4 At the end of 1982,
the combined notional principal outstanding for interest rate and currency swaps stood at $5 billion.
Notional principal is the face value of the underlying
debt upon which swap cash flows are based.
FEDERAL RESERVE BANK OF ATLANTA
The commodity swap made its appearance in
1987, when it was approved by a number of U.S.
banking regulators (see Schuyler K. Henderson 1990
and Krystyna Krzyzak 1989b, c). Banks had been
prohibited from direct transactions in commodities or
related futures and forward contracts. In 1987 the Office of the Comptroller of the Currency permitted
Chase Manhattan Bank to act as a broker in commodity swaps between an Asian airline and oil producers. Shortly afterward Citicorp also obtained
approval for engaging in commodity swaps through
its export-trading subsidiary. Regulations were further
relaxed in February 1990 to allow national banks to
use exchange-traded futures and options to hedge
commodity swap positions. However, much commodity swap activity took place offshore because of
uncertainties about the Commodity Futures Trading
Commission's (CFTC) view of commodity swaps. The
CFTC undertook a study of off-exchange transactions
in February 1987 to determine whether they came
under the CFTC's regulatory jurisdiction. In July 1989
the CFTC established criteria that would exempt commodity swaps from its regulatory oversight.5 Since
the CFTC's decision commodity swap activity has
been increasing in the United States. As of early 1990,
commodity swaps outstanding totaled about $10 billion in terms of the value of the underlying commodities (Julian Lewis 1990, 87).
Equity swaps are the newest variety, first introduced in 1989 by Bankers Trust. Based on both domestic and foreign stock indexes, these instruments
may take complex forms, such as paying off the
greater of two stock indexes against a floating rate of
interest. The mechanics of such instruments and
their advantages will be discussed below.
The Size o f the Market. As of year-end 1989, the
size of the worldwide swaps market, as measured by
the dollar value of the notional principal, stood at
$2.37 trillion. This figure does not include commodity or equity swaps, but these new types of swap
have relatively small amounts outstanding compared
with interest rate and currency swaps. The International Swap Dealers Association (ISDA), a trade organization, periodically surveys its members, who include
most of the major swap dealers. Table 1 displays the
survey results for swaps in various categories. The
The author is an economist in the financial section of the
Atlanta Fed's research department. He is grateful to many
people in the swaps market for assistance with his research
for this article. He would particularly like to thank Charles
W. Smithson and fames M.F. MeVay of Chase Manhattan
Bank and Ron Slivka of Salomon Brothers. However, any
errors are the author's responsibility.
13
Table 1
U. S. Dollar Interest Rate Swaps
1985-89*
Survey Period
1985
1986
1987
1988
1989
Total
ISDA User
End User
Contracts
Notional
Principal
Average
Contract
Contracts
Notional
Principal
Average
Contract
Contracts
Notional
Principal
Average
Contract
5,918
10,752
16,871
20,381
23,324
$141,834
$235,829
$379,880
$484,272
$622,602
$23.97
$21.93
$22.52
$23.76
$26.69
1,061
3,330
7,472
8,968
13,303
$28,348
$76,921
$161,637
$243,894
$371,144
$26.72
$23.10
$21.63
$27.20
$27.90
6,979
14,082
24,343
29,349
36,627
$170,182
$312,750
$541,517
$728,166
$993,746
$24.38
$22.21
$22.25
$24.81
$27.13
$19.95
$23.49
$23.15
34,127
49,560
73,828
$682,888
$1,010,203
$1,502,600
$20.01
$20.38
$20.35
Total Interest Rate Swaps
1987-89
1987
1988
1989
23,768
35,031
50,193
$476,247
$668,857
$955,492
$20.04
$19.09
$19.04
* All dollar amounts are in millions of dollars in U.S. dollar equivalents.
Source: International Swap Dealers Association Market Survey.
10,359
14,529
23,635
$206,641
$341,345
$547,108
interest rate swap market, involving swaps denominated in one currency, composed roughly two-thirds
of the market, or $1.5 trillion as of year-end 1989. Of
that amount, two-thirds consisted o f U.S. dollar
swaps, the most prevalent kind of swap. The average contract size was $20.35 million and $27.13 million for total and total dollar interest rate swaps,
respectively. Currency swap market data are given in
Table 2. The U.S. dollar is less dominant among currency swaps, for which it represents 41 percent of
the total, compared with its 66 percent share of interest rate swaps. For the years during which the survey has been conducted, swaps of every type have
grown rapidly. ^
In all categories the position of the end users has
been a multiple of those of the swap dealers. Interdealer swaps arise mainly in connection with hedging activities. A certain amount of double counting is
therefore involved in the aggregate figures because
one swap can set u p a number of others as counterparties hedge their positions.
The latest ISDA survey reveals that the most active
category for new swaps originated during the period
January 1 to June 30, 1990, was non-U.S. dollar interest rate swaps, which grew by 26.4 percent. U.S. dollar swaps increased by 8.2 percent in this period. In
contrast, total currency swaps rose by 2.9 percent,
with U.S. dollar currency swaps contracted increasing by 4.6 percent. These semiannual growth rates
show considerable variability over time and thus do
not indicate trend movements. Further discussion of
the ISDA survey results appears below in the section
on currency swaps.
Interest Rate Swaps
Interest rate swaps account for the most volume
in the swaps market, as seen in the previous section.
The explanation to follow covers many of the numerous features that can modify the plain vanilla
swap. Though discussed in detail only in relation to
interest rate swaps, these alternate forms actually or
potentially apply to currency, commodity, and equity
swaps as well; they can be combined in innumerable
ways to alter any kinds of cash flows.
The basic fixed-for-floating interest rate swap involves a net exchange of a fixed rate, usually expressed as a spread over the Treasury bond rate
corresponding to the swap maturity, for a floating
rate of interest. That floating rate is tied or indexed
to any of a number of short-term interest rates. The
London Interbank Offered Rate (LIBOR) is the most
common. 7 Other rates include the Treasury bill rate,
FEDERAL RESERVE BANK O F ATLANTA
the prime rate, the Commercial Paper Composite, the
Certificate of Deposit Composite, the federal funds
rate, the J.J. Kenney index, and the Federal Home
Loan Bank System's Eleventh District cost-of-funds
index. The Eleventh District index has been used
mainly by thrift institutions in California. 8 The J.J.
Kenney index is based on short-term tax-exempt
municipal bond yields.
The fixed rate payer (and floating rate receiver) is
said to have bought a swap or to have "gone long" a
swap. Similarly, the floating rate payer (and fixed rate
receiver) is said to have sold a swap or "gone short"
a swap. Swaps are quoted by a dealer (or broker)
usually in terms of the spread over the Treasury security of comparable maturity. For example, a swap
with seven-year time to maturity, or tenor, might be
quoted at 65-72. The dealer is offering to buy a swap
(pay fixed) at a rate that is 65 basis points above the
seven-year Treasury yield, and offering to sell a swap
(receive fixed) at 72 basis points over that yield.9 The
dealer is therefore collecting a 7 basis point margin
for standing between the counterparties.
Like floating rate notes, the floating rate payments
on a swap do not necessarily match the timetable of
the floating rate index. 10 The payment may be based
on the average of the underlying index during some
specified interval. The point at which the floating
rate is established, based on the floating rate at that
time or over some previous period, is termed the reset date. This date is not necessarily the same as the
settlement date, when payment on the swap is made
to the other counterparty. If reset and settlement
dates do not coincide, the swap is said to be paid in
arrears, which is also a c o m m o n convention for
floating rate notes. The floating rate may be reset
daily, weekly, monthly, quarterly, or semiannually,
while typically the settlement dates fall monthly,
quarterly, semiannually, or annually (Anand K. Bhattacharya and John Breit 1991, 1158).
As over-the-counter instruments, interest rate
swap terms are open to negotiation. The conventional way to quote a swap rate is relative to the floating
rate index "flat." That is, a swap counterparty would
pay the fixed rate and receive LIBOR. Swaps can also be arranged to include a spread above or below
the floating rate—for example, LIBOR + 10 basis
points. In addition, fixed rate payers and floating rate
payers can agree to making payments at different
periods—quarterly floating rate payments versus
semiannual fixed rate payments. 11 However, swap
counterparties usually prefer net transactions so that
only a difference check passes between them, thereby limiting credit exposure. In the section below the
first alteration of the basic plain vanilla structure that
is considered encompasses different treatments of a
15
Table 2
U. S. Dollar Currency Swaps
1987-89*
Survey Period
Contracts
Notional
Principal
1987
1988
1989
4,665
6,777
9,078
$129,181
$201,374
$257,748
Total
ISDA User
End User
Average
Contract
$27.69
$29.71
$28.39
Contracts
Notional
Principal
Average
Contract
Contracts
Notional
Principal
Average
Contract
1,366
2,297
3,414
$33,425
$68,103
$96,418
$24.48
$29.66
$28.24
6,031
9,074
12,492
$162,606
$269,477
$354,166
$26.96
$29.70
$28.35
$24.67
$32.30
$27.67
6,612
10,271
15,285
$365,614
$633,642
$869,698
$27.65
$30.85
$28.45
Total Currency Swaps
1987-89
1987
1988
1989
5,173
7,724
11,270
$294,608
$469,092
$647,516
$28.47
$30.37
$28.73
* All dollar amounts are in millions of dollars in U.S. dôllar equivalents.
Source: International Swap Dealers Association Market Survey.
1,439
2,547
4,015
$71,006
$164,550
$222,182
swap's notional principal. The second general variation outlined allows for specially tailored coupon
structures, and the discussion includes consideration
of option-like features. Third, different types of underlying instruments—in particular, asset swaps and
their uses in creating synthetic assets—are examined.
Finally, option structures are discussed, including
options on swaps, known as swaptions.
Seasonal Swaps and Roller Coasters. Finally, amortizing and accreting notional principals can be combined to form a seasonal swap, which allows the
notional principal to vary according to a counterparty's seasonal borrowing needs such as those retailers
typically experience. A swap that allows for periodic
or arbitrary but predictable swings in notional principal is called a roller coaster.
V a r i a t i o n s o n N o t i o n a l P r i n c i p a l . The plain
vanilla swap is nonamortizing. Nonamortizing
swaps, known as "bullet" swaps, have a constant
underlying notional principal upon which interest
payments are made. This structure is easily modified
to accommodate any kind of predictable changes in
the underlying principal. Uncertainty about the future amount of the principal, which frequently arises
with mortgage-backed securities, is usually better
handled using option features, which will be discussed shortly.
Variations o n C o u p o n Payments. Altering cash
flows of underlying securities is one of the primary
functions of swaps. In the following section a number of important types of swaps that accomplish this
end are discussed, including those with option-like
features.
Off-Market Swaps. The plain vanilla swap is also
characterized as a par value swap. That is, the fixed
rate for the swap is established such that no cash
payment changes hands when the swap is initiated.
The term par value derives from the swap's being
viewed as a hypothetical exchange of fixed for floating rate bonds. When arranged at market interest
rates, both bonds are equal to their face values (par
value). Nonpar, or off-market, swaps involve fixed or
floating rates that are different from the par value
swap rates. Differences in the fixed rate above or below the par value swap rate entail a cash payment to
the fixed rate payer from the floating rate payer if
the fixed rate coupon is above the par value swap
rate, and vice versa if it is below. The payment's
amount is the present value of the difference between the nonpar and par value swap fixed rate
payments. Swap counterparties commonly perform
this kind of calculation in the process of marking an
existing swap to market. An existing swap may be
terminated (if permitted in the swap agreement) by
such a marking to market of the remaining swap
payments. High or low coupon swaps, as off-market
swaps are alternatively called, are created simply by
doing the calculation at the outset and making or receiving the appropriate payment. One reason for engaging in this type of swap is to change the tax
exposure of underlying cash flows. Another is that
spreads above or below the floating rate index can
be introduced. John Macfarlane, Janet Showers, and
Daniel Ross (1991) explain the mechanics of this
variation.
Amortizing, Annuity, and Mortgage Swaps. Amortizing swaps are typically used in conjunction with
mortgage loans, mortgage-backed securities, and automobile- and credit-card-backed securities. All of
these tend to involve repayment of principal over
time. In general it is difficult to match the amortization schedule of a swap, which usually cannot be
changed after its initiation, against the amortization
rate on these assets or liabilities; thus, the swapholder runs the risk of being over- or underhedged. A
particular example of an amortizing swap is discussed in more detail in the section below on asset
swaps. One specific kind is the mortgage swap,
which is simply an amortizing swap on mortgages or
mortgage-backed securities. The extreme form of an
amortizing swap, in which the notional principal diminishes to zero as the principal of a fixed rate mortgage does, is an annuity swap.
Accreting Swaps. The flip side of an amortizing
swap is an accreting swap, which, as its name suggests, allows the notional principal to accumulate
during the life of the swap. Both amortizing and accreting swaps are sometimes also called sawtooth
swaps. The accreting swap arises commonly with
construction finance, in which a construction company or developer has a floating rate drawdown facility
with a bank. That is, a line of credit may be tapped
that would lead to increasing amounts of floating
rate borrowing. An accreting swap would convert
those floating rate payments into fixed rate payments, although again there is a risk of not exactly
matching notional principal amounts at each settlement date. It is possible to create amortizing or accreting swaps from bullet swaps of varying tenor
instead of arranging a swap specifically with the desired characteristics.
FEDERAL RESERVE BANK OF ATLANTA
Basis Swaps. A basis swap is an exchange of one
floating rate interest payment for another based on
a different index. Consider an example in which a
bank, First SmartBucks, has invested in two-year
floating rate notes that pay the bank one-month
LIBOR plus 100 basis points. First SmartBucks has
funded this purchase by issuing one-month certificates of deposit. The problem is that LIBOR and the
CD rate will not track each other perfectly, exposing
17
First SmartBucks to a so-called basis risk; it may pay
more on its CDs than it receives from its floating rate
notes. The problem is solved by entering into a basis
swap with a swap dealer, who will pay the onemonth CD rate in exchange for LIBOR. Chart 1 illustrates the transaction. Aside from the initial fee for
the swap, the cost of this hedging transaction manifests itself as a 10 basis point spread under the CD
rate received from the dealer. This hedge may also
be less than perfect, however, because the dealer
probably would use the Certificate of Deposit Composite, which may not track First SmartBucks's CD
rate perfectly, to index his payments. Nevertheless,
the swap is likely to mitigate the original basis risk.
Yield Curve Swaps. The yield curve swap, a variant
of the basis swap, typically is an exchange of interest
payments indexed to a short-term rate for ones tied to
a long-term rate. For example, a counterparty could
contract to make semiannual floating rate payments
based on six-month LIBOR and receive floating rate
payments indexed to the prevailing thirty-year Treasury bond yield, less a spread to the swap dealer.12
The ten-year Treasury bond yield has also been used
for yield curve swaps on the long end, as well as
three-month LIBOR on the short end.
Yield curve swaps gained popularity in early 1988
when the yield curve began to flatten—that is, when
long rates fell relative to short rates (Krzyzak 1988,
29). Savings and loan institutions were major users
of this new swap because they found it useful for
adjusting the interest rate exposures of their portfolios (see asset swaps below). These swaps were also
well suited to speculating on shifts in the yield curve
while hedging against changes in its level. Finally,
these instruments were combined with a new kind
of floating rate debt, called FROGs (floating rate on
governments), to transform the FROG's coupon into
LIBOR. The coupon was reset semiannually and tied
to the yield on newly issued Treasury bonds. 13 This
strategy reportedly achieved a lower cost of funding
than a standard LIBOR floating rate issue.
Caps, Floors, and Collars. A floating rate payer
can combine option contracts with a swap to tailor
the maximum size of potential swap payments. Interest rate caps, floors, and collars are instruments
closely related to swaps that can alter swap cash
flows. 14 As an example, consider a plain vanilla
swap with a fixed rate of 8 percent (the swap rate).
At a reset date, a rise in the floating rate above 8
percent would obligate the floating rate payer to pay
the counterparty the net amount of the notional principal outstanding times the difference between the
actual floating rate—say, 10 percent—and the swap
rate. By buying a 9 percent cap of the same maturity
as the swap the user would never pay more than
one percentage point above the swap rate. The cap
could be obtained from another counterparty, or it
could be bundled with the swap in one transaction.
However, buying a cap from another counterparty
introduces an additional credit risk.
Chart 1
A Basis Swap
LIBOR
Swap Dealer
First SmartBucks
C D Composite Rate
-10 Basis Points
l1
LIBOR
+ 100
Basis
Points
CD
Rate
r
Assets
Liabilities
FRNs
CDs
First SmartBucks transforms LIBOR interest coupons into CD composite rate payments via a basis swap.
18
ECONOMIC REVIEW, »MARCH/APRIL 1991
A counterparty who sells (or writes) a cap is obligated to pay the excess over the cap's strike rate
(9 percent in this example). The purchaser in return
pays a cap "premium" up front. In fact, caps are sequences of interest rate options with maturities that
match the schedule of floating rate payments. Analogous to caps, interest rate floors pay off whenever
the floating interest rate falls below the prespecified
floor level. To defray some or all of the cost of buying a cap, the floating rate payer could sell a floor
with a strike rate less than the swap rate. Such a sale
would create an interest rate collar. Thus, rather than
paying for the protection of the cap outright, the
floating rate payer could give up part of the payments from the swap resulting from large declines in
the floating rate below the swap rate. That is, the
maximum possible payment from the other swap
counterparty would effectively be the difference of
the swap rate and the floor strike rate times the notional principal.
Synthetic Swaps. The "collaring" of a swap suggests that a floating rate payer could completely offset a swap by buying a cap and selling a floor that
both have strike rates equal to the swap rate. Similarly, a fixed rate payer could nullify a swap by selling
a cap and buying a floor with strike rates equal to
the swap rate. In these cases the floating rate payer
would, in effect, be buying a "synthetic" swap and
the fixed rate payer would be selling one. However,
swaps are not usually unwound in this way because
it is generally cheaper simply to buy or sell the corresponding swap; caps and floors may not be sufficiently liqCiid at the desired strike rates to execute
these transactions at reasonable prices. (That is, an
illiquid—infrequently traded—cap or floor would be
quoted with large spreads.) Nevertheless, arbitrage
between the swap and cap/floor markets is possible
and does occur if rates for these instruments get too
far out of line.
Participating Swaps. A hybrid version of the fixed
rate swap and interest rate cap allows a counterparty
to benefit partially from declining rates while not requiring any up-front payment as with a cap. Consider an example using LIBOR. The counterparty would
receive LIBOR to pay its floating rate debt. In turn,
instead of paying a fixed interest rate as for a plain
vanilla swap, a higher fixed rate is established
(above the swap rate), which is the maximum rate
the counterparty would pay if LIBOR rises above
that level. However, if LIBOR falls below this maximum rate, the counterparty's payment would decline
less than one-for-one with LIBOR. For example, the
swap terms could stipulate that a one percentage
point drop in LIBOR would reduce the swap payment by one-half percentage point. The so-called
FEDERAL RESERVE BANK O F ATLANTA
participation rate in this case is 50 percent. In other
words, the counterparty would participate in 50 percent of any decline in LIBOR below the maximum
rate. The maximum rate and the participation rate
are set to price the swap at zero cost upon initiation.
The price of this swap's option feature is paid by
giving up part of the gains from falling rates.
The participating swap can also be structured to
have the counterparty pay LIBOR and receive payments indexed to a fixed schedule. That is, a minimum rate would be specified in the swap, with
payments above that minimum determined by the
product of the prevailing LIBOR multiplied by the
participation rate. A counterparty might want to use
such a swap in conjunction with its floating rate assets. Participating swaps can be structured for any
interest rates and are also used for currencies and
commodities.
Reversible Swaps and Roller Coasters. Reversible
swaps and roller coasters are a couple of exotic variants on swap structures. A reversible swap allows a
counterparty to change status from floating rate payer to fixed rate payer or vice versa at some point
during the life of the instrument. The roller coaster
takes this concept a step further by having the counterparties reverse roles at each settlement date. Distinct from the earlier type of roller coaster involving
variations in notional principal, this one has been
used in only a limited number of transactions.
Zero Coupon Swaps. As its name implies, all payments on one side of the swap come at the end in
one "balloon" payment, while the other side makes
periodic fixed or floating rate payments. One use of
zero coupon swaps is to transform the cash flows
from zero coupon bonds into those of fixed coupon
bonds or floating rate bonds, or vice versa.
Asset S w a p s . Asset swaps are precisely what
their name suggests. They effectively transform an
asset into some other type of asset, such as the conversion of a fixed rate bond into a floating rate
bond. The conversion results in synthetic securities
because of the swap's effects. The analysis of asset
swaps actually contains nothing new. The earlier example of First SmartBucks's use of a basis swap, exchanging LIBOR for the CD Composite rate, was a
type of asset swap. Asset swaps are usually considered in connection with portfolio management and
are low-cost tools for changing the characteristics of
individual securities or portfolios.
Bhattacharya (1990) discusses an interesting application of asset swaps to a particular kind of
mortgage-backed security. The collateral behind
mortgage-backed securities is subject to prepayment. For example, homeowners may pay off their
mortgage principals early in the event they move
19
or mortgage rates drop sufficiently. Collateralized
Mortgage Obligations (CMOs) repackage mortgage
cash flows into a variety of securities that carry different prepayment risks. Planned Amortization Class
(PAC) bonds are structured to have amortization
schedules more predictable than those of other CMO
classes. However, the risks are nevertheless sufficient
to make PAC bonds trade at fairly wide spreads over
corresponding Treasury securities. PAC bonds have
been popular candidates for amortizing asset swaps
that convert the bonds' fixed coupons into floating
rate payments tied to any index. These asset swaps
have the potential to make PAC bonds attractive to a
broader class of investors and consequently channel
more funds to the mortgage market. Such swaps may
be a more cost-effective means of altering the characteristics of mortgage-backed securities than having an
even broader array of such securities being issued.
As a tool for bond portfolio management, asset
swaps can change a portfolio's exposure to interest
rate risk. The value of a portfolio, and of any bonds
within it, fluctuates with shifts in interest rates,
tending to fall as market rates rise and vice versa.
The sensitivity to interest rate risk is measured by a
portfolio's duration, which is based on the future
timing and size of its cash flows.15 A portfolio manager can extend a portfolio's duration, increasing its
volatility with respect to interest rate movements, by
entering into asset swaps to receive fixed rate cash
flows and to pay floating rate cash flows. Conversely, a portfolio can be protected or "immunized"
against interest rate movements by contracting to
make fixed rate cash flows and receive floating rate.
The intuition here is that the more a portfolio's (or
security's) cash flows move with current market
rates, the closer its value will stay to face value.
Money market funds, for example, experience little
change in asset value because they have very short
duration. In contrast, a fund consisting of long-term
zero coupon bonds, which have durations equal to
their maturities, would have extremely volatile asset
values.
Asset swaps are particularly useful for adjusting a
portfolio when securities sales would result in capital
losses. For example, a portfolio manager would be
reluctant to change the portfolio's duration by selling
off bonds that are "under water" (currently valued
below par). As just discussed, an asset swap is ideal
for this kind of adjustment.16 As another example,
some bonds cannot be traded because they were
purchased from an underwriter through a private
placement to avoid registration and other costs associated with public issues. Using an asset swap obviates the need to trade the underlying security to alter
interest rate exposure.
20
F o r w a r d a n d E x t e n s i o n S w a p s . Forward
swaps are analogous to forward or futures contracts as hedging instruments. The difference is that
forward or futures contracts hedge cash flows at a
single point in the future whereas forward swaps
(and swaps generally) hedge streams of cash flows.
Extension swaps are an application of forward
swaps.
Forward Swaps. Financial managers, such as corporate treasurers, often want to hedge themselves
against rising interest rates when considering a future debt issue. For example, selling a new issue of
bonds may be necessary to refund outstanding corporate bonds that mature in one year. The yield on
that issue is unknown today but could be locked in
using a forward or deferred swap. If rates have risen
when the outstanding bonds mature, the firm sells
the swap, realizing a gain equal to the present value
"As a tool for bond portfolio management, asset swaps can change a portfolio's exposure to interest rate risk."
o f the difference b e t w e e n the cash flows b a s e d o n
the current s w a p rate a n d those b a s e d o n the l o w e r
fixed rate o f the forward s w a p . This gain w o u l d offset the higher c o u p o n p a y m e n t s o n the n e w l y issued
fixed rate b o n d ; the effective rate p a i d w o u l d b e the
s a m e as the forward s w a p rate.
H o w e v e r , a fall in rates w o u l d translate into a loss
o n the forward s w a p u p o n sale, a l t h o u g h the n e w l y
i s s u e d fixed rate b o n d w o u l d itself carry a l o w e r
rate. T h e effective rate o n the fixed rate issue w o u l d
a g a i n b e the f o r w a r d s w a p rate, neglecting differences in transactions costs. T h e forward s w a p in this
e x a m p l e is u s e d as a h e d g i n g tool, establishing a
certain fixed rate today instead o f a n u n k n o w n fixed
rate at the future date for d e b t issuance.
Extension
Swaps.
A n extension s w a p is merely a
f o r w a r d s w a p a p p e n d e d to a n existing s w a p before
its term e n d s t o e x t e n d it b y s o m e a d d i t i o n a l p e r i o d
(Jeffry B r o w n 1991, 127). If the forward s w a p is arr a n g e d b a s e d o n current f o r w a r d interest rates, the
ECONOMIC REVIEW, »MARCH/APRIL 1991
extension swap w o u l d be obtained at n o cost.
However, if a counterparty wants the forward swap
rate to match an outstanding swap's rate, an upfront cash payment (or receipt) might be necessary
to compensate for the change in market rates since
the outstanding swap's origination. The extension
swap in this case would be a type of off-market
swap.
Swaptions. The earlier discussion of amortizing
swaps and the example of an asset swap involving a
PAC bond emphasized the risk inherent in mismatches of principal with notional principal. The
amount of principal is not always perfectly predictable, especially for many new types of assetbacked securities. Option contracts are designed to
handle contingencies of this kind, and, not surprisingly, a market has developed for options on swaps,
known as swaptions. (There is also a market for op-
"For hedging applications,
perhaps
the swaption's
most basic use is to
give a swap counterparty the option to
cancel a swap, at no further cost beyond the initial swaption
premium."
tions on caps and floors, which, as one might guess,
are called captions and floortions.)
Like any option, swaptions entail a right and not
an obligation on the part of the buyer. Unfortunately, the nomenclature for swaptions is confusing, so
the details are often simply spelled out in talking
about them. A call swaption (a call option on a swap
or payer swaption) is the right to buy a swap—pay a
fixed rate of interest and receive floating. A put
swaption (put option on a swap or receiver swaption) is the right to sell a swap—pay floating and receive fixed. The swaption on the plain vanilla swap
is the most common, although swaptions can be
written on more complicated swaps. Both the maturity of the swaption and the tenor of the underlying
swap, which commences at a stipulated future date,
must be specified. Also like options, swaptions come
in both American and European varieties. The European swaption, which accounts for about 90 percent
of the market, may be exercised only upon its matu-
FEDERAL RESERVE BANK OF ATLANTA
rity date, whereas the American swaption may be
exercised at any time before maturity (Robert
Tompkins 1989, 19). Only European swaptions will
be considered in this discussion, unless otherwise
noted.
A call swaption would be exercised at maturity
if the swaption strike rate—the fixed rate specified
in the contract—is lower than the prevailing market fixed rate for swaps of the same tenor. The
swaption could be closed out by selling the low
fixed rate swap obtained through the swaption for
a gain, rather than entering into that swap. Similar
reasoning applies to the decision to exercise a put
swaption.
Swaptions are quite different from caps and
floors, although these instruments are frequently
used in similar situations. A swaption involves one
option on a swap, while a cap (or floor) represents a
series of options expiring at different dates on a
floating interest rate. In addition, cap prices depend
partly on the volatility of near-term forward rates,
whereas swaption prices reflect the volatility of future swap rates, which in turn are averages of more
distant, less volatile forward rates. Consequently,
swaptions are much cheaper than caps or floors.
Like options, swaptions require up-front payments,
but these have recently fallen in the range of 20-40
basis points as compared with 200-300 basis points
for caps or floors (Krzyzak 1989a, 13). American
swaptions would be slightly more costly than European swaptions because of the additional right to exercise the instrument before maturity.
Callable, Puttable, and Reversible Swaps. For
hedging applications, perhaps the swaption's most
basic use is to give a swap counterparty the option
to cancel a swap, at no further cost beyond the initial swaption premium. A fixed-for-floating swap
bundled together with a put swaption is known as
a callable swap. The swap can be canceled upon
the maturity of the embedded swaption if, for example, interest rates have fallen. Exercising the
swaption creates an offsetting floating-for-fixed
swap. A floating-for-fixed swap combined with a
call swaption is called a puttable swap. The swap
can be terminated if interest rates have risen—that is,
if a higher fixed rate could be received from a new
swap.
Another example of a swaption application involves the PAC bond considered earlier. The amortizing swap to pay fixed and receive floating could
be hedged against the possibility that the rate of
amortization is faster than that structured in the
swap. A put swaption purchased along with the original fixed-for-floating swap would (partially) hedge
this risk. The purchaser would buy a swaption(s) in
21
the amount necessary to partially offset the underlying
swap in order to cover the potential additional amortization of principal. An American swaption would be appropriate for this application.
The reversible swap described earlier can be synthesized by a fixed-for-floating plain vanilla swap
combined with put swaptions for twice the notional
principal of the underlying swap. Assuming a swaption has the same notional principal amount as the
swap, the first swaption cancels the existing swap
and the second creates a floating-for-fixed swap upon maturity, running for the remaining term of the
original swap.
Extendable Swaps. As the name suggests, an extendable swap contains the option to lengthen its
term at the original swap rate. Such a swap simply
amounts to an ordinary swap with a swaption expiring at the end of the swap's tenor. Note the difference between an extendable swap and an
extension swap. The former gives the holder the
option to extend a swap; the latter is a commitment. The same distinction applies to swaptions
and forward swaps.
Leveraged Buyout Hedging. Another application of
swaptions has been in leveraged buyouts, in which a
firm's management takes on large amounts of debt
to "take a firm private." Lenders, such as commercial
banks, often require the firm to hedge its debt,
which typically is floating rate. A call swaption with
a strike rate at a level the firm could safely meet
would accomplish this end. Should the floating rate
rise sharply, the swaption would be exercised, converting the remaining floating rate payments to manageable fixed rate payments. However, lenders
involved in leveraged buyout financing often prefer
to sell caps because a swaption, if exercised, makes
its writer a counterparty to a highly leveraged (and
often low-rated) firm. A cap writer faces no credit
risk from the cap buyer.
Synthetic Straight Debt. A final example of swaption usage is in stripping callable debt. This strategy
has been popular in the swaption market's brief history. Corporate bonds are frequently issued with options allowing the issuer to refinance the debt issue
at a lower coupon if interest rates fall before the
bonds mature. The issuer usually cannot exercise
the embedded call until after some prespecified
date. The callable debt's buyer has effectively written a call option on the price of the bond to the issuer, the firm. If bond prices rise above the strike
price of the calls (implying that interest rates have
fallen sufficiently), the issuer has the right to call the
bonds away after paying the strike price.
Because many participants in these markets have
believed that the calls attached to these bonds are
22
undervalued, the following arbitrage strategy developed. Firms wanting fixed rate debt issued callable
bonds and "stripped" the embedded call options by
selling call swaptions, with the net result of creating
synthetic noncallable or "straight" bonds at a lower
yield than that prevailing on comparable fixed rate
bonds. The yield reduction stemmed from selling the
undervalued bond market calls at a profit in the
swap market.17
As an illustration of the basic strategy, assume the
bond is callable at par. That is, if at the call date the
relevant interest rate is at or below the original
coupon rate, the bond will be called. To strip the
call option, the issuer writes a put swaption, which,
if exercised, obligates the firm to pay fixed and receive floating on a swap commencing on the bond's
first call date and ending at the bond's maturity
date. In this example the swaption strike would be
set to the bond's coupon rate. If interest rates fall,
the put swaption is exercised. In turn, the firm
would call its debt and simultaneously issue floating
rate debt, whose coupon payments would be met
by the floating rate payments coming from the swap
counterparty. On balance, the firm would continue
to make fixed rate payments, though to the swap
counterparty instead of to the bondholders. There
are many variations on this strategy. Also, embedded put options can be stripped from bonds in a
similar way. 18
The Size of the Swaption Market. As of year-end
1989, $79.7 billion in U.S. dollar and non-U.S. dollar
swaptions was outstanding, as measured by the value
of the underlying notional principal. 19 The market
grew 118 percent compared with the figure for yearend 1988, the first year the survey included swaptions.
The size of the caps, collars, and floors market was
considerably larger. For year-end 1989, the total U.S.
dollar and non-U.S. dollar value of the notional principal for caps, collars, and floors was $457.6 billion,
representing a 57 percent increase over the previous
year's figure.
Non-U.S. D o l l a r D e n o m i n a t e d Interest Rate
S w a p s . The interest rate swap market is active
worldwide. About one-third of interest rate swaps
outstanding involved currencies other than the
U.S. dollar. Table 3 reports the latest International
Swap Dealers Association survey results for yearend 1989 reflecting swaps involving a single currency. The dollar e q u i v a l e n t of the n o t i o n a l
principal outstanding is shown, ranked by currency. The Japanese yen is a distant number two to
the U.S. dollar, accounting for 8.5 percent of the
market. The British pound and deutsche mark are
next in order, with the New Zealand dollar ranking last.
ECONOMIC REVIEW, »MARCH/APRIL 1991
Table 3
Interest Rate Swaps
as of December 31,1989*
Currency
U.S. Dollar
Equivalent
End-User
Counterparty
(percent)
U.S. Dollar
Yen
Sterling
Deutsche Mark
Australian Dollar
French Franc
Canadian Dollar
Swiss Franc
European Currency Unit
Dutch Guilder
Hong Kong Dollar
Belgian Franc
New Zealand Dollar
$993,746
$128,022
$100,417
$84,620
$67,599
$42,016
$29,169
$28,605
$18,988
$5,979
$2,149
$835
$444
62.65
52.25
60.13
61.46
84.35
89.92
87.66
55.65
58.51
65.14
60.12
79.16
82.66
ISDA
Counterparty
(percent)
Currency
as Percentage
of Total
($1,502.6 billion)
37.35
47.75
39.87
38.54
15.65
10.08
12.34
44.35
41.49
34.86
39.88
20.84
17.57
66.14
8.52
6.68
5.63
4.50
2.80
1.94
1.90
1.26
.40
.14
.06
.03
* All dollar amounts are in millions of dollars in U.S. dollar equivalents.
Source: International Swap Dealers Association Market Survey.
Currency Swaps
Basic currency swaps were described earlier in
connection with their evolution from parallel loan
agreements. The fixed-for-fixed currency swap is the
most rudimentary type of swap and is roughly
equivalent to a series of forward foreign exchange
contracts. For example, a firm could borrow yen at
a fixed interest rate and swap its yen-dominated
debt for fixed rate dollar-denominated debt. The exchange rate for converting cash flows throughout
the life of the swap would be established at the outset. Forward foreign exchange contracts, if they
were available in long-dated maturities, could also
lock in the exchange rate for future cash flows.
All of the features enumerated for interest rate
swaps can be applied singly or in combination to
swaps involving different currencies. A number
of applications of currency swaps are discussed
below.
Currency C o u p o n Swaps. One of the currency
swap's early variants is the currency coupon swap,
otherwise known as the cross-coupon swap. This
swap is like a plain vanilla swap in which the fixed
interest rate is paid in one currency while the floating
FEDERAL RESERVE BANK OF ATLANTA
rate is paid in another. However, the principal involved in the transaction is usually exchanged as well.
An Example. Consider a hypothetical transaction
between a U.S. firm, USTech, and a British bank, BritBank. A U.S. swap dealer intermediates the transaction, in part because this institution has the relevant
credit information about the swap counterparties that
they lack individually. USTech is setting up a British
subsidiary and issuing dollar-denominated floating
rate bonds tied to LIBOR to finance this operation.
USTech wants to hedge itself on two counts, though:
first, it wants protection against foreign exchange rate
fluctuations because the subsidiary's sales revenue
will be in sterling but will be needed to service the
dollar-denominated floating rate debt; second,
USTech prefers to make fixed rate payments. A currency coupon swap would enable the firm to make
sterling-denominated fixed rate payments while receiving dollar-denominated LIBOR, which it would
pass to its floating rate bondholders. O n the other
hand, BritBank would like sterling-denominated fixed
rate cash flows instead of dollar-denominated LIBOR
payments from floating rate notes that it holds in a
portfolio within its trust department. The bank wants
the fixed rate sterling cash flows to extend the duration of its portfolio.
23
As is typical of currency swaps, this one involves
exchanges of principal at the beginning and end of
the swap. The dealer collects his margin on the fixed
rate side of the swap. Like the fixed rate currency
swap, the exchange rate for the currency coupon
swap is established at the outset and prevails at each
of the subsequent settlement dates. Payments at
those dates are for the gross amounts of the cash
flows, not the net amount as with interest rate
swaps, although some swaps stipulate that net
amounts be exchanged.
European Currency Unit Swaps. The European
Currency Unit (ECU) has become an increasingly
important "currency" in the Eurobond market. If
progress is made toward monetary union of the
European Community (EC), the ECU may become
European markets' official unit of account. It currently is valued as a weighted average of twelve
EC currencies. Although growing rapidly, the number of outstanding ECU-denominated bonds constitutes only about 4 percent of the outstanding
amount of publicly issued Eurobonds (Graham
Bishop 1991, 72.) Cross-coupon ECU swaps have
been used to transform both principal and coupon
payments denominated in the ECU into other currencies and vice versa.
Terry Shanahan and Jim Durrant (1990) discuss an
example in which a U.S. multinational firm needed
to finance subsidiaries in France, Belgium, and the
Netherlands. The firm borrowed in the Eurobond
market by floating ECU-denominated fixed rate debt
and converted the issue via a cross-coupon swap into floating rate debt with payments in French francs,
Belgian francs, and Dutch guilders. The firm exchanged the principal, consisting of a basket of currencies in proportion to each currency's share in the
ECU, raised from the bond buyers. In return, the firm
received an equivalent value of the three currencies
from the swap counterparty. During the life of this
five-year swap, the firm received annual ECU
coupon payments from the counterparty, which the
firm passed on to the bondholders, and it made annual floating rate payments in guilders and Belgian
francs and semiannual floating rate payments in
French francs to the counterparty. Upon maturity of
the swap, the initial transfer of principal was reversed. The counterparty exchanged ECU principal
for repayment in the three currencies from the U.S.
firm. In turn, the firm redeemed its bonds with the
ECU payment from the counterparty.
S w a p p i n g I l l i q u i d B o n d s a n d Private Placements. A major impetus for the growth of currency
swaps has been and continues to be the portfolio
management of illiquid securities. The earlier discussion of portfolio duration adjustment showed a
24
basic rationale for u s i n g s w a p s , w h i c h h o l d s particularly true i n t h e E u r o b o n d m a r k e t , w h e r e
many
b o n d s lack the liquidity to b e traded readily. I n add i t i o n , for i n t e r n a t i o n a l l y diversified
portfolios,
b o n d trading m a y b e desired t o c h a n g e portfolios'
e x p o s u r e s to e x c h a n g e rate
fluctuations.
Currency
s w a p s fulfill portfolio m a n a g e r s ' n e e d s for s u c h risk
management.
Currency (and interest rate) swaps have been especially useful in managing portfolios of privately
placed bonds. In terms of a number of costs to the
issuer, these bonds are significantly cheaper than
publicly placed bonds. Use of privately placed
bonds avoids the public disclosure and registration
requirements as well as compliance with U.S. accounting regulations; it also minimizes legal costs,
reduces underwriting costs, and speeds placement.
Yet such securities appeal to a much narrower class
of investors because of their illiquidity.
In April 1990 the Security and Exchange Commission approved Rule 144A, which greatly simplifies
disclosure requirements for private placement issuers
(Franklin Chu 1991, 55). Non-U.S. corporations that
need to fund their U.S. subsidiaries will find it much
easier to raise capital through private placements.
The disadvantages of holding these relatively illiquid
securities is expected to be lessened both by the use
of swaps in portfolio management and by the
growth of a secondary market for private placements
(Brady 1990, 86).
The Size o f the Market. The U.S. dollar is the
preeminent currency in the currency swaps market.
Table 4 shows that the dollar has a 41 percent share
in the currency swaps market, followed by the
Japanese yen with a 23 percent share. The Swiss
franc, Australian dollar, and German mark occupy
the next ranks, with the Hong Kong dollar taking
the smallest share of the market for the surveyed
currencies.
Commodity Swaps
Commodity swaps are straightforward extensions
of financial swaps, though a number of institutional
factors make commodity swapping much riskier than
the financial variety. As mentioned earlier, only
about $10 billion in notional value has been transacted in this relatively new market. However, commodity prices historically have been much more volatile
than financial asset prices, and volatility tends to
promote the development and use of hedging instruments. Commodity swaps' volume has reportedly
doubled in the past year and is expected to do so
E C O N O M I C REVIEW, »MARCH/APRIL 1991
Table 4
Currency Swaps
as of December 31, 1989*
Currency
U.S. Dollar
Yen
Swiss Franc
Australian Dollar
Deutsche Mark
European Currency Unit
Sterling
Canadian Dollar
Dutch Guilder
French Franc
New Zealand Dollar
Belgian Franc
Hong Kong Dollar
U.S. Dollar
Equivalent
End-User
Counterparty
(percent)
ISDA
Counterparty
(percent)
Currency
as Percentage
of Total
($869.7 billion)
$354,166
$201,145
$64,823
$61,768
$53,839
$39,948
$33,466
$32,580
$10,132
$8,435
$5,818
$2,997
$583
72.78
71.83
77.42
70.77
79.93
83.06
74.11
81.72
82.53
88.74
81.90
86.89
90.39
27.22
28.17
22.58
29.23
20.07
16.94
25.89
18.28
17.47
11.26
18.10
13.11
9.61
40.72
23.13
7.45
7.10
6.19
4.59
3.85
3.75
1.17
.97
.67
.34
.07
* All dollar amounts are in millions of dollars in U.S. dollar equivalents.
Source: International Swap Dealers Association Market Survey.
again in 1991 ( J a n e t Lewis 1990, 207). Another impetus is likely to be the resolution of some regulatory
uncertainties, as discussed above. Energy-related
commodities hedged via swaps to date include
crude oil, heating oil, gasoline, naphtha, natural gas,
jet fuel, maritime diesel fuel, and coal. Swap maturities have ranged from one month to five years. A
relatively smaller number of swaps have been arranged for gold and for base metals, mainly copper
and aluminum, as well as a few in nickel and zinc
(Brady 1990, 87).
cost of the hedge. In contrast, over-the-counter oil
swaps are well suited to hedging intermediate-term
risks that cannot be handled by simple positions in
futures having relatively short maturity. At the same
time, the implication is that swap intermediaries face
greater risks because of difficulties they encounter in
hedging their swap positions (see Janet Lewis 1990).
Oil trading firms have an advantage in acting as
dealers because they also carry out transactions in
the underlying commodities, giving them additional
flexibility in hedging.
The most popular commodity swap has been the
plain vanilla fixed-for-floating swap, very much akin
to the plain vanilla interest rate swap. End users turn
to swaps for hedging for essentially the same reasons that they take positions in commodity futures
contracts. Their pricing decisions can be based on a
known future cost of inputs or revenue from outputs, allowing the appropriate margins to be built in.
The end users avail themselves of hedging instruments to transfer the risk to others who specialize in
managing that risk.20 Exchange-traded futures and
options contracts tend to be liquid for contracts with
time to maturity of only a few months. Hedging
large positions farther out in time would cause the
futures prices to move against the hedger, raising the
A commodity swap may be important as a hedge
for a firm that is considering financing a project using debt.21 The same is true for interest rate and currency swaps as well, but commodity prices are
notoriously volatile, giving lenders ample reason to
require a commodity swap hedge.22 In other words,
swaps can increase a firm's ability to borrow.
A n E x a m p l e . A U.S. producer of oil, TexOil,
Inc., sells oil at the spot price but wants to hedge
against any large drops in the price of oil that
would make production uneconomical. Another
counterparty, a charter luxury liner company, LuvBoats Ltd., wants to hedge the proceeds from advanced ticket sales for the coming year. Maritime
diesel fuel, purchased at the spot price, is a major
FEDERAL RESERVE BANK OF ATLANTA
25
operating cost for LuvBoats's ships. Chart 2 depicts a
pair of plain vanilla swaps with a swap dealer intermediating the transaction.
As with any kind of swap transaction, a dealer
does not necessarily need an offsetting counterparty
to enter into a swap with another counterparty. The
swap involving LuvBoats Ltd. is actually tied to the
price of No. 2 heating oil, which is a more actively
traded commodity than maritime diesel. The spread
to the counterparty is lower because the swap dealer
can better hedge its position, for example by using
No. 2 heating oil futures contracts. LuvBoats is willing to bear some basis risk—the risk that maritime
diesel and heating oil price movements will be less
than perfectly correlated—to avoid paying the dealer
a larger spread to index a swap to the price of maritime diesel. TexOil receives a fixed price of $25 per
barrel of crude from the swap dealer, while LuvBoats
pays a fixed amount of 74 cents per gallon of heating oil. Since the swap's origination, oil and refined
product prices have declined, resulting in a $4.52 per
barrel net payment to TexOil and a 9 cent per gallon
net payment from LuvBoats at the current payment
date.
Oil swaps can assume more complex forms. For
example, they can be combined with currency and
interest rate swaps to convert uncertain, dollardenominated spot market purchases of oil into fixed
deutsche mark payments. To meet regulatory guidelines, commodity swaps require the inclusion of caps
and floors, although these are usually set at prices
far from the prevailing commodity price and thus are
unlikely to be reached. Caps, collars, floors, participating swaps, swaptions, and many other instruments have been adapted to the commodity markets.
Also, oil and other commodity swaps typically reset
based on daily averages of spot market prices for the
underlying commodity. Averaging tends to make the
floating side of a swap have a better correspondence
with actual spot market purchases by the counterparties. A swap reset based on a single day's price
would be less likely to be representative of such
purchases.
Equity Swaps
Equity swaps are the newest type of swap and
are a subset of a new class of instruments known as
synthetic equity. 23 Equity swaps generally function
as an asset swap that converts the interest flows on
a bond portfolio into cash flows linked to a stock
index. The stock indexes that have been used include the Standard and Poor's (S&P) 500, the Tokyo
Stock Price Index (TOPIX) and Nikkei 225 (Japan),
the Chambre des Agents de Change (CAC) 240
(France), the Financial Times Stock Exchange
(FTSE) 100 (United Kingdom), the Toronto Stock
Exchange (TSE) 300 (Canada), as well as others (see
Chart 2
Commodity Swaps
Crude Oil Swap
No. 2 Heating Oil Swap
TexOil receives $25 per barrel and pays the spot price for crude oil. LuvBoats receives the spot price for No. 2
heating oil and pays a fixed price for heating oil. LuvBoats in turn buys maritime diesel at the spot price for diesel.
There are 42 gallons in a barrel.
26
E C O N O M I C REVIEW, »MARCH/APRIL 1991
Salomon Brothers, Inc. 1990; Saul Hansell 1990; and
Richard Metcalfe 1990, 40). Linking portfolio performance to an index means that dividends are not received as with actual equity ownership; the portfolio
tracks only the capital gain component of the underlying stocks.
One of the advantages of using a synthetic swap
is that transactions costs are mitigated, especially in
dealing w i t h less l i q u i d foreign stock markets
(Hansell 1990, 56). O n the other hand, such swaps
are also illiquid, which implies that their use be
predicated on a buy-and-hold strategy for an investment portfolio. Equity swaps have been structured to
have one- to five-year tenors and usually have quarterly or semiannual reset dates.
The mechanics of an equity swap are similar to
the workings of other kinds of swaps. Typically, an
investor will swap either fixed or floating rate interest payments for payments indexed to the performance of a stock index such as the S&P 500. If the
index appreciates during the interval between settlement dates, the investor receives a payment from
the counterparty equal to the rate of appreciation
times the swap's notional principal. At the same
time, the investor pays, for example, LIBOR less a
spread representing the margin to the dealer. Actual
settlement would involve only the difference between these bases. In the event the S&P 500 falls,
the investor w o u l d pay the rate of depreciation
times notional principal and LIBOR less a spread.
O f course, the investor is receiving LIBOR or another floating rate from his or her investment portfolio.
The net result of the swap is that the portfolio's income behaves like that of an index equity portfolio.
A variation of the basic equity swap—the asset allocation swap—links the equity side of the swap to
the maximum of two indexes. For example, the
swap agreement could stipulate that the counterparty
receive the maximum of the rate of appreciation (or
pay the maximum rate of depreciation) on the S&P
500 or Nikkei 225 at each settlement date. This kind
of swap effectively swaps a portfolio into a foreign
stock portfolio or domestic stock portfolio instantly,
without transactions costs (apart from those associated with the swap). There are many other possibilities for asset allocation swaps. As another example,
the swap could be indexed to the maximum of the
S&P 500 or a bond index. Index options could be
embedded in the swaps to trade away upside exposure in exchange for downside protection from index moves.
FEDERAL RESERVE BANK O F ATLANTA
Conclusion
Swaps are but one kind of instrument that has
been spawned in the profusion of financial innovation during the last two decades.24 In the most general terms, swaps are contracts that transform cash
flows from underlying assets or liabilities. They have
been designed to incorporate great flexibility in that
task and hence are frequently described as instruments that tailor cash flows. This article encompasses the four basic types of swap: interest rate,
currency, commodity, and equity. Each group in turn
branches into a variety of forms that can accommodate virtually any application. However, novelty
does not guarantee success. The most successful
swaps have frequently been the simplest, plain vanilla variety.
Swaps integrate credit markets. By the nature of
their function, swaps can link money markets (shortterm financing) and capital markets (long-term financing). Swaps also play a significant role in the
so-called globalization of financial markets because
they obviate the need for many investors to carry out
transactions in underlying foreign securities, thereby
contributing to the international diversification of
portfolios. International arbitrage of securities and
swaps markets is left to those participants w h o have
the lowest transactions costs, increasing global market efficiency.
Swaps are an important tool for simplifying financial transactions that cross national borders. At the
same time, they pose potential risks to the stability
of financial markets. Recent concern about the
strength of both banks and investment banks has focused the attention of swap market participants on
counterparties' creditworthiness, upon which the financial obligations contracted through a swap agreement depend.2"5
However, part of the reason that swaps evolved
was to reduce the credit exposure of counterparties
involved in similar financial arrangements. Swaps
generally confine credit risk to exposure to the net
difference in cash flows, not the gross amounts or
exposure of underlying principal, and defaults have
been rare occurrences.26 The implementation of the
Basle Agreement in 1992 will establish more uniform
capital standards for the world's commercial banks
and should help to further reduce credit risks in the
swap market. 27
27
Notes
1. Shirreff (1989) reports that swaps with thirty-year maturities or "tenors" have been arranged. Such long-lived
swaps typically involved counterparties with top credit
ratings or relied on third-party credit enhancements.
2. Wall and Pringle (1988) discuss the plain vanilla swap
in detail and consider the reasons for using swaps.
3. A forward contract commits the buyer to purchase the
underlying asset at a prespecified price (the forward
price) u p o n maturity of the contract. A call option
gives the buyer the right, but not the obligation, to
purchase an underlying asset at a prespecified price on
or sometime before the maturity date of the option.
The put gives the corresponding right to sell at a prespecified price. These instruments will be described
further at appropriate places in the exposition.
may also be used for this purpose. Brown and Smith discuss many subtleties of these strategies.
18. Krzyzak (1988, 29; 1989a, 9) reports that the embedded
calls were overvalued and that call monetization was
used to undo the expensive call. In this case, call monetization would not be an arbitrage.
19. Chew (1991) discusses recent activity in the non-U.S.
dollar swaptions markets, particularly deutsche mark
instruments.
20. This point of view is not universal or uncontroversial.
Williams (1986) argues that risk aversion has nothing to
d o with the use of futures. Rather, futures contracts reduce transactions costs in dealing with underlying
commodities. His model assumes that all futures market participants are risk neutral.
4. See McNulty and Stieber (1991) for a more detailed account.
5. See Henderson (1990) for details about the CFTC's criteria.
21. Also, Smith, Smithson, and Wilford (1990) discuss a
conflict between stockholders and bondholders of a
corporation, known as the underinvestment problem,
that swaps can mitigate.
6. The growth may be exaggerated by these figures because the number of survey respondents, not reported
in the tables, has also been increasing. However, the
ISDA points out that the major swap dealers have consistently participated in their surveys.
22. See Spraos (1990) for a case study of a complex copper swap required in part for this reason.
7. See Kuprianov (1986) for a background discussion of
Eurodollar futures and LIBOR.
8. See McNulty and Stieber (1991, 100-101) for information about the Eleventh District cost-of-funds rate.
9. A basis point is a hundredth of a percentage point.
10. Ramaswamy and Sundaresan (1986) analyze floating
rate securities and discuss the characteristics of such
securities.
11. See Macfarlane, Showers, and Ross (1991) for a discussion of nonstandard swap terms. This article gives a
detailed account of swap terminology and conventions.
12. Ordinarily, comparisons of yields along the yield curve
are made using instruments of comparable default risk.
Yield curve swaps exchange floating payments on debt
bearing different default risks. Because the underlying
three-month Eurodollar time deposit is default risky,
LIBOR is greater than the riskless three-month Treasury
bill yield. The swap therefore exchanges credit spreads
as well as yield curve spreads.
13. See G o o d m a n (1991, 160-61) for details about this
strategy.
14. See Abken (1989) for an introduction to these instruments.
15. See Bodie, Kane, and Marcus (1989) for an introduction to duration analysis.
16. This example is cited by Bhattacharya (1990, 56).
17. Goodman (1991) and Brown and Smith (1990) discuss
call monetization using several strategies. Forward swaps
28
23. Other examples of synthetic equity include over-thecounter equity options, public warrant issues, and
bonds containing equity options. See Hansell (1990).
Index-linked certificates of deposit were a retail form
of synthetic equity offered by a number of commercial
banks and savings and loans in 1987.
24. See Finnerty (1990) for a comprehensive survey of financial innovations since the 1970s.
25. Krzyzak (1990) and Brady (1991) describe the concerns
and difficulties experienced by low-rated swap dealers
in dealing with higher-rated counterparties. See Abken
(1991) for a model of swap valuation in which swaps
are subject to default by the participating counterparties.
26. Aggarwal (1991) reports several sources giving a figure
of $35 million in write-offs resulting from swap defaults
as of year-end 1988. The collapse of Drexel, Burnham,
Lambert in 1989 brought with it potential defaults on
its swap book. Most o f these swaps were closed out or
rearranged with other swap dealers, avoiding defaults
that would have shaken the swaps market. See Perry
(1990) for an account of the Drexel collapse and its aftermath on the swaps market. Evans (1991) reports that
U.S. and foreign banks face potential defaults of u p to
SI billion because of to a British court ruling that nullifies swap contracts with about 80 British municipalities.
27. See Wall, Pringle, and McNulty (1990) for a discussion
of the Basle Agreement and its treatment of swaps under the new capital standards. Levis and Suchar (1990)
give further discussion and detailed examples.
E C O N O M I C REVIEW, MARCH/APRIL 1991
References
Abken, Peter A. "Interest-Rate Caps, Collars, and Floors."
Federal Reserve Bank of Atlanta Economic Review 74
(November/December 1989): 2-24.
. "Valuation of Default-Risky Interest-Rate Swaps."
Federal Reserve Bank of Atlanta working paper, forthcoming, 1991.
Aggarwal, Raj. "Assessing Default Risk in Interest Rate
Swaps." In Interest Rate Swaps, edited by Carl R. Beidleman, 430-48. H o m e w o o d , 111.: Business O n e Irwin,
1991.
Bhattacharya, Anand K. "Synthetic Asset Swaps." Journal
of Portfolio Management 17 (Fall 1990): 56-64.
, and J o h n Breit. "Customized Interest-Rate Risk
Agreements and Their Applications." In The Handbook
of Fixed Income Securities, 3d ed., edited by Frank J.
Fabozzi, 1157-89- Homewood, 111.: Business O n e Irwin,
1991.
B i s h o p , G r a h a m . "ECU Bonds: Pioneer o f Currency
Union." Euromoney (January 1991): 7Iff.
Bodie, Zvi, Alex Kane, and Alan J. Marcus. Investments.
Homewood, 111.: Richard D. Irwin, Inc., 1989.
Brady, Simon. "How to Tailor Your Assets."
Euromoney
(April 1990): 83-89.
. "Time Runs O u t for Low-Rated Swappers." Euromoney (February 1991): 9-10.
Brown, Jeffry P. "Variations to Basic Swaps." In Interest
Rate Swaps, edited by Carl R. Beidleman, 114-29.
Homewood, 111.: Business O n e Irwin, 1991Brown, Keith, and D o n a l d J. Smith. "Forward Swaps,
Swap Options, and the Management of Callable Debt."
Journal of Applied Corporate Finance 2 (Winter 1990):
59-71.
Chew, Lillian. "Strip Mining." Risk 4 (February 1991): 20ff.
Chu, Franklin J. "The U.S. Private Market for Foreign Securities." Bankers Magazine (January/February 1991): 55-60.
Evans, John. "British Court Rules Swaps by Municipalities
Illegal." American Banker, January 25, 1991, 13.
Finnerty, John D. "Financial Engineering in Corporate Finance: An Overview." In The Handbook of Financial
Engineering, edited by Clifford W. Smith and Charles
W. Smithson, 69-108. Grand Rapids, Mich.: Harper
Business, 1990.
Goodman, Laurie S. "Capital Market Applications of Interest Rate Swaps." In Interest Rate Swaps, edited by Carl
R. Beidleman, 147-74. Homewood, 111.: Business O n e
Irwin, 1991.
Hansell, Saul. "Is the World Ready for Synthetic Equity?"
Institutional Investor (August 1990): 54-61.
H e n d e r s o n , Schuyler K. "A Legal Eye o n H e d g i n g ' s
Newest Club." Euromoney (May 1990): 95-96.
Krzyzak, Krystyna. "Don't Take Swaps at Face Value." Risk
1 (November 1988): 26-31.
. "Swaptions Deciphered." Risk 2 (February 1989a):
9-17.
. "From Basis Points to Barrels." Risk 2 (May 1989b):
. " S w a p s Survey: A r o u n d the H o u s e s . " Risk 3
(September 1990): 51-57.
Kuprianov, Anatoli. "Short-Term Interest Rate Futures."
Federal Reserve Bank of Richmond Economic Review
(September/October 1986): 12-26.
Levis, Mario, and Victor Suchar. "Basle Basics." Risk 3
(April 1990): 38-39.
Lewis, Janet. "Oil Price Jitters? Try Energy Swaps." Institutional Investor (December 1990): 206-8.
Lewis, Julian. "The Bandwagon Starts to Roll." Euromoney
(May 1990): 87-94.
Macfarlane, John, Janet Showers, and Daniel Ross. "The
Interest-Rate Swap Market: Yield Mathematics, Terminology, and Conventions." In Interest Rate Swaps, edited by Carl R. Beidleman, 233-65. H o m e w o o d , 111.:
Business O n e Irwin, 1991.
McNulty, James E., and Sharon L. Stieber. "The Development and Standardization of the Swap Market." In Interest Rate Swaps, edited by Carl R. Beidleman, 97-113Homewood, 111.: Business O n e Irwin, 1991.
Metcalfe, Richard. "Out of the Shadows." Risk 3 (October
1990): 40-42.
Perry, Phillip M. "Drexel Redux? Credit Quality Is a Hot
Topic." Corporate Risk Management (May/June 1990):
27-29.
Ramaswamy, Krishna, and Suresh M. Sundaresan. "The
Valuation of Floating-Rate Instruments: Theory and Evidence." Journal of Financial Economics 17 (December
1986): 251-72.
Salomon Brothers, Inc. "Equity-Linked Index Swaps." Sales
brochure, 1990.
Shanahan, Terry, and Jim Durrant. "Driving Factors." Risk
10 (November 1990): I4ff.
Shirreff, David. "Where Others Fear to Tread." Risk 8
(September 1989): 11-16.
Smith, Clifford W., Charles W. Smithson, and Lee Macdonald Wakeman. "The Evolving Market for Swaps." In
The Handbook of Financial
Engineering,
edited by
Clifford W. Smith and Charles W. Smithson, 191-211.
Grand Rapids, Mich.: Harper Business, 1990.
Smith, Clifford W., Charles W. Smithson, and D. Sykes
Wilford. "Financial Engineering: Why Hedge?" In The
Handbook of Financial Engineering, edited by Clifford
W. Smith and Charles W. Smithson, 126-37. Grand
Rapids, Mich.: Harper Business, 1990.
Spraos, Paul B. "The Anatomy of a Copper Swap." Corporate Risk Management 2 (January/February 1990): 8, 10.
Tompkins, Robert. "Behind the Mirror." Risk 2 (February
1989): 17-23Wall, Larry D., and John J. Pringle. "Interest Rate Swaps: A
Review of the Issues." Federal Reserve Bank of Atlanta
Economic Review 73 (November/December 1988): 22-37.
8-12.
Wall, Larry D., J o h n J. Pringle, and James E. McNulty.
"Capital Requirements for Interest-Rate and Foreign-Exchange Hedges." Federal Reserve Bank of Atlanta Economic Review 75 (May/June 1990): 14-27.
. "Copper-Bottomed Hedge." Risk 2 (September
1989c): 35-39.
Williams, Jeffrey. The Economic Function of Futures Markets. New York: Cambridge University Press, 1986.
FEDERAL RESERVE BANK OF ATLANTA
29
FYI: The Impact of Private-Sector
Defense Cuts on Regions of the
United States
David D. Whitehead
n light of the reduced threat of a major conflict with the Soviet Union, both Congress
and the administration last year acknowledged the opportunity to cut national defense expenditures. Because defense s p e n d i n g
constituted 24 percent of all government outlays and
slightly more than 5 percent of the gross national
product in 1990, even small cuts could have significant negative effects on employment of workers producing military goods and support services as well
as the locales in which they work. Assessing the potential effects of the defense cuts proposed in the
1992 Bush administration budget is the purpose of
this article. The focus is on the short-term, initial
consequences for employment in various regions of
the country. Longer-term employment results of
eliminating defense-related jobs and redistributing
government defense savings throughout the economy are beyond the scope of this study.1
I
Background on Proposed Defense Cuts
In the early 1970s, following the Vietnam War, real
(inflation-adjusted) defense outlays declined rather
rapidly and then stabilized at middecade, remaining
fairly constant from 1975 through 1980. The end of
The author is the research officer in charge of the regional
section of the Atlanta Fed's research department.
30
the Carter administration and the beginning of Reagan's presidency saw double-digit nominal percent
increases in defense outlays, resulting in an increase
of real outlays. That increase continued throughout
most of the Reagan years, reaching a plateau at the
$240 billion to $250 billion range (in 1982 dollars)
for fiscal year (FY) 1986 through FY 1990. It is from
this level that the administration and Congress are
currently proposing cuts.2
Table 1 (page 35) shows the budgeted cuts in
nominal defense outlays for 1991 through 1995. To
demonstrate the relative magnitude of the cuts, the
1992 budget presents them as a reduction from a
nominal spending level that would have maintained
1990's real defense spending level, providing a
baseline. For instance, actual defense expenditures
in 1990 amounted to $299 billion. Those same purchases in 1991 would have cost $307 billion—an $8
billion difference representing an increase of 2.6
percent. The percentage implied by the budget
document is the 1991 rate of inflation in defense
item prices. Expenditures totaling less than $307
billion would reflect a reduction in the real level of
expenditures. The budget calls for defense outlays
of $299 billion in 1991—the same dollar figure as in
1990. However, because of inflation this amount
represents a reduction of 2.6 percent in constant
dollars.
For 1992 the baseline for constant real defense
expenditures converts to $318 billion in 1992 dollars,
some $19 billion, or 6.4 percent, more than the 1990
figure. The 1992 budget calls for defense outlays of
$295 billion, a cumulative decline of 7.2 percent
ECONOMIC REVIEW, »MARCH/APRIL 1991
from the $318 billion that would equal the 1990 level
of defense purchases. This amount represents a 4.6
percent reduction, in real terms, from 1991. By 1995
the cumulative cuts from the 1990 baseline will
amount to a 17.4 percent reduction in real defense
outlays—$182 billion, with almost one-third called
for in 1995.
A reduction in real outlays implies a likely nearterm loss of employment for those producing the
eliminated goods or services. Cutting defense spending, no matter how it is accomplished, will affect
economic activity throughout the nation, but the impact will be felt most acutely by regions and local
communities that have been highly dependent on
Defense Department expenditures.
Regional Impact of Defense Cuts
As acknowledged earlier, estimating the overall
consequences of defense spending reductions would
require a complex analysis outside the scope of this
article. The initial effect on employment in each state
or region targeted for Defense Department spending
cuts can more reasonably be approximated. However, the extent to which the current employment levels will be affected depends on decisions about
specific base closings, realignments, and overall reductions in troop levels.
Direct employment generated by defense spending can be divided into three general categories: military personnel, Department of Defense civilian
personnel, and civilian workers employed as a direct
result of defense purchases from private-sector firms.
The number of workers in the first two categories is
easily measured and their various locations identified. The first two columns of Table 2 (pages 36-37)
indicate active duty military and Department of Defense civilian personnel in 1988 for each state and
census region.3 As discussed in the box on page 32,
anticipated base closings and realignments are expected to have little effect on employment. Because
overall reductions in troop levels depend on a number of factors, any projection about the effects of
such reductions—accomplished primarily through attrition, curtailed recruitment, and distribution of
these cuts according to a set of unknown military
priorities—would be highly speculative at this point.
No direct measure of the third category—privatesector defense-related employment—is available, but
estimates can be based on Department of Defense
"prime contract awards." These contracts are a measure of certain expenditures that, like others, generate income and employment. If one accepts the
FEDERAL RESERVE BANK OF ATLANTA
assumption that related employment is distributed
in the same way as prime contract dollars, the relationship between these expenditures, which are reported on a state-by-state basis, and resulting
employment can be roughly approximated. It is true
that this assumption injects some error into the estimates because various types of contracts are not distributed uniformly across states. In addition, some of
the work associated with prime contract awards may
be subcontracted to out-of-state firms. Although
these points are troublesome for estimating local effects, numerous studies confirm that contract awards
are sufficiently detailed to identify the location of
most production and that subcontract work flows in
both directions—into and out of a state—largely offsetting any impact. Thus, estimating the geographic distribution o f e m p l o y m e n t o n the basis o f
prime contract awards appears to be a reasonable
approach. 4
The third column of Table 2 shows estimates of
the level of private-sector defense-related employment based on the average value of contracts awarded to private firms in each state during the period
1986 to 1988. The three-year average is used because
contracts awarded in one year are usually not completed in a single twelve-month interval and therefore
do not represent that year's actual outlays. Each
state's percentage of total prime contract awards in
the nation is calculated and then used to allocate to
each state its share of the estimated 3,400,000 jobs
supported annually by prime contracts awarded nationwide. 5 For example, Connecticut received an average of 3.9 percent of all prime contract awards in
the nation during FY 1986-88—134,018 of the nation's private-sector defense-related jobs.
In terms of major census regions, 1988 estimates place the highest concentrations of privatesector defense workers in the South (32 percent)
and the West (30 percent). Far exceeding all other
states, California contains more than 19 percent of
the nation's total. More important than these workers' location is each area's dependence on privatesector defense employment. The sixth column of
Table 2 shows private-sector defense-related employment as a percentage of total employment in
census regions, subregions, and states. O f major
census regions, the West and Northeast are most
economically dependent on these jobs. In terms of
subregions, New England has the highest proportion of private-sector defense jobs—5.9 percent of
the area's total e m p l o y m e n t . The Pacific area
ranks second highest in terms of shares of these
workers, and the South Atlantic and West North
Central subregions third. Least d e p e n d e n t o n
private-sector defense-related employment is the
31
Direct Employment Impact of Base Closings
nation. While the Northeast, North Central, and West
census regions will all lose employment under the 1988
legislation, the South will gain, but only marginally.
In January 1990, just as the first round of base closings began, the Department of Defense proposed a second round of base closings involving thirty-five bases
and the realignment of forces at several dozen more.
These recommendations have not been acted upon.
Congress instead adopted legislation establishing a
commission that may accept or amend the Department
of Defense's base-closing recommendations before
passing them on to the president. The president then
has fifteen days to pass the recommendations to
Congress for approval or rejection. He may recommend
either approval or rejection of the list.
Legislation passed in 1988 cleared the way to close
or realign military bases in various areas of the nation,
thereby directly affecting military and civilian base
workers. The legislation targeted eighty-six bases for
closing, five for partial closing, and fifty-four for realignment involving either expanding or downgrading
military and civilian employment. In terms of net employment, 12,900 military and 7,742 civilian workers are
expected to be affected nationwide. Total numbers of
active duty military or Department of Defense civilian
workers are less than 1 percent.
The table below lists the sixty-six bases slated to
lose or gain 100 or more employees. With a net loss of
more than 11,000 and 17,000 jobs, respectively, the
West and, more specifically, California will be hardest
hit. In 1988 California housed more than 204,000 active
duty military personnel and more than 130,000 Department of Defense civilian workers, significantly more
than any other state. The state's loss equals 5 percent of
those employees in its borders, compared with a loss of
less than a 1 percent nationwide. However, these figures represent a very small part of the total employment picture—one-tenth of one percent in California
and less than two one-hundredths of one percent in the
This new process was set in motion on April 12,
1991, when Defense Secretary Cheney recommended
closing thirty-one major military bases and twelve minor installations as well as realignment of twenty-eight
others. Because these most recently proposed closings
and realignments are still speculative at this point, even
a ball-park estimate of potential losses or gains they
may create in direct military or Department of Defense
civilian employment is virtually impossible.
Bases Gaining or Losing 100 or More Employees under the 1988 Legislation,
Aggregated by State and Census Region
Region
Number of Bases
by Service
Net Employment Change
Military
Net Employment Change
Civilian, P O D 1
Total Net
Employment Change
-761
1,633
872
NORTHEAST
Massachusetts
2 Army
New Hampshire
1 Air Force
-2,250
-400
-2,650
N e w Jersey
3 Army
-3,199
-1,525
-4,724
N e w York
1 Air Force
2 Navy
101
3
104
Pennsylvania
2 Army
1 Navy
-442
812
370
-6,551
523
-6,028
-3,116
-2,637
-5,753
600
319
919
1
100
101
300
52
352
-2,215
-2,166
-4,381
TOTAL NORTHEAST
NORTH CENTRAL
Illinois
1 Air Force
2 Army
Indiana
Michigan
Missouri
TOTAL N O R T H CENTRAL
32
2 Army
1 Army
1 Army
ECONOMIC REVIEW, MARCH/APRIL 1991
Number of Bases
by Service
Net Employment Change
Military
Net Employment Change
Civilian, DOD 1
Total Net
Employment Change
SOUTH
Kentucky
2 Army
265
-1,056
-791
Louisiana
1 Navy
-338
-24
-362
Maryland
2 Army
-88
-181
-269
Mississippi
1 Air Force
114
77
191
South Carolina
1 Army
661
126
787
Texas
3 Air Force
1 Army
2 Navy
1,683
380
2,063
Virginia
3 Army
146
-986
-840
2,443
1,664
779
TOTAL S O U T H
WEST
Arizona
1 Air Force
2 Army
-783
-62
-845
California
6 Air Force
3 Navy
2 Army
-12,817
-4,507
-17,324
1 Air Force
545
-5
540
2,267
30
2,297
1,859
90
1,949
1,448
195
1,643
-3
-161
-164
-26
-159
-185
894
144
1,038
-6,616
-4,435
-11,051
-12,939
-7,742
-20,681
Colorado
2 Army
Hawaii
Idaho
New Mexico
Oregon
Utah
Washington
1 Navy
1 Air Force
2 Air Force
1 Army
2 Army
2 Air Force
2 Navy
1 Army
TOTAL WEST
TOTAL U N I T E D STATES
1
U.S. Department of Defense.
Source: Calculated by the Federal Reserve Bank of Atlanta from data in Congressional Quarterly Almanac 44 (1988): 442-43.
East North Central subregion, where these jobs
account for only 1.5 percent of total employment.
At the state level, those with a high dependence
on private-sector defense employment will, of
course, be affected by defense spending cuts. While
private-sector defense-related work accounts for 3-0
percent of employment nationally, such jobs make
FEDERAL RESERVE BANK O F ATLANTA
up more than 4 percent of total employment in ten
states and the District of Columbia. The latter leads
with 10.6 percent of its workers in such jobs. Connecticut and Massachusetts show the second and
third greatest dependencies on defense expenditures
to support private-sector jobs, contributing to New
England's position as the most dependent subregion.
33
Statistics on the geographic concentration of
workers and reliance on defense spending for
private-sector employment reveal little about an
area's ability to absorb employment dislocations that
may result from defense spending cuts. The effects
of these reductions could be mitigated by the vitality
and diversity of local economic activity. Therefore, to
identify areas most likely to suffer relatively larger
and longer employment dislocations, one must determine the time it will take to integrate those affected back into the economy as productively employed
workers. Two major factors are the rate at which
new jobs are being created in an area and the transferability of displaced workers' skills to nondefense
business activity. The absorption of these workers
will also depend on demand in occupations producing civilian goods and services.
The number of dislocated workers relative to employment growth in an area provides a standardized
measure of how quickly a state or region may be able
to reabsorb these individuals into the ranks of the employed. Additionally, assessing the types of activities
involved in defense-related jobs may help evaluate,
albeit roughly, the versatility of a worker's abilities.
For instance, a steel worker and an office worker will
have developed different skills, some perhaps more in
demand by other employment sectors.
An absorption rate is simply the number of potentially dislocated workers divided into the net amount
of new employment in an area during a given time
period (hereafter used to refer to one year). In direct
relationship, slower total employment growth results
in a lower absorption rate for the same absolute
number of dislocated workers. The higher the annual absorption rate, the lower the number of displaced workers relative to employment growth and
the easier it should be for these workers to find alternative jobs in a given area.
The first and second columns of Table 3 (pages
38-39) show the number of private-sector defense-related workers that could be dislocated annually in
each state and region if these cuts are spread proportionately over all regions. The third c o l u m n
shows the state's annual change in total employment
for 1988-89, a recent and not unusual year for economic growth. The fourth and fifth columns show
the number of times in a given year that the assumed dislocated workers could be absorbed into
the work force based on the area's employment
growth from 1988 to 1989- For example, a 3 percent
annual cut in real defense spending would displace
an estimated 102,000 workers nationwide in one
year. Total annual average employment in the nation
grew by 2.3 million from 1988 to 1989- Therefore,
the estimated number of workers displaced in 1989
34
could have been absorbed almost twenty-three
times. With a 6 percent cut, the rate of absorption
w o u l d fall by 50 percent to slightly higher than
eleven.
Table 3 suggests that the Northeast will have
more difficulty than the rest of the nation dealing
with the employment impact of defense budget
cuts. New England's absorption rate of 2.9 percent
is significantly smaller than all other subregions', as
expected in light of the area's dependence on defense spending. The West North Central and Middle Atlantic subregions also show absorption rates
significantly lower than the nation's. If relative absorption rates hold, the two areas least likely to be
negatively affected by defense cuts are the East
North Central and East South Central, each showing absorption rates two to three times the national
average.
The five states most likely to suffer severely because of defense outlay cuts are Connecticut, Massachusetts, Virginia, Missouri, and Colorado. For the
times measured, these states typically have had a
larger-than-average share of employees tied to defense and a comparatively slow rate of overall employment growth. In Connecticut 8 percent of total
employment is estimated to be civilian defense-related.
In Massachusetts the figure is 7 percent, and in Virginia, 6.7 percent. Missouri, with 6 percent of its total e m p l o y m e n t private-sector defense-related,
ranks fourth, and Colorado ranks tenth with 4 percent.
Texas, New York, and Florida also have relatively
large shares of total defense purchases—4 to 7 percent—but their private-sector defense employment
as a percent of total employment is smaller than in
the states identified above. Across the board, defense
cuts even at the 6 percent level will have only
marginal impact on most local economies, while a
few states will be rather hard hit.
The other significant indicator of the difficulty an
area will have in assimilating dislocated workers
back into the labor force lies in the types of jobs
likely to be affected. Defense-related civilian employment nationwide tends to be concentrated in
durable manufacturing activities. Based on prime
contract awards, Table 4 (page 40) shows the percentage of total Department of Defense nonwage
and salary expenditures flowing to the six industries
receiving the greatest shares of these monies. Aircraft
and parts, ordnance and accessories, and other transportation equipment (basically shipbuilding and repair)—heavy manufacturing activities—account for
approximately 35 percent of all Defense Department
direct purchases from the private sector. Radio, television, and communications equipment, classified as
ECONOMIC REVIEW, MARCH/APRIL 1991
light manufacturing, represents almost 20 percent of
total private-sector direct defense expenditures,
while business services and new construction represent 13 percent and 5 percent, respectively.
The portions of these various industries' expenditures differ significantly among the four main census
regions. For instance, business services and radio,
television, and communications equipment constitute
the largest shares of private-sector direct defense
spending in the South. This configuration is in sharp
contrast to the North Central region, which receives
the major share of spending for aircraft and parts
and ordnance and accessories.
The general level of local economic activity certainly contributes to how long workers remain unemployed if defense-related jobs are discontinued. As
observed earlier, each worker's versatility of skills is
also a factor. Those who have experience easily transferable to private-sector production are more likely to
shift to producing private-sector goods at the same
firm or at another. For example, nonmanufacturing
constitutes a larger proportion of private-sector jobs,
so nonmanufacturing skills tend to be easier to transfer to private-sector employment.6 Workers with skills
unique to the defense sector or little used in privatesector operations will find it harder to find alternative
employment.
Examining the composition of civilian defenserelated employment in each of the five states that
defense cuts are likely to affect the most can provide clues about the degree of difficulty workers
may face in seeking new positions. For these states,
which receive the highest portion of prime contract
awards, Table 5 (page 40) indicates the percentages
of total expenditures in the six industries. The figures suggest the share of defense-related civilian
employment associated with each industry in these
states, even though the relationship between expenditures and number of workers differs by industry.
For instance, in Virginia defense dollars tend to flow
more toward—and, it is assumed, generate more employment in—business services than the other categories. This concentration of defense dollars
suggests, of course, that if defense cuts are proportional across industry lines Virginia will feel the
strongest employment influences in this sector.
Along with Virginia, Colorado derives more service-sector employment from defense expenditures
than do the three other states included in Table 5.
Because the skills associated with service jobs can
usually be transferred, the dislocation shocks in
these two states will probably be less severe than in
the other three states. Connecticut and Missouri are
the states most dependent on manufacturing-related
Table 1
National Defense Outlays, FY 1991-95
(billions of dollars)
1991
1992
1993
1994
1995
July 1990 Gramm-Rudman-Hollings
Baseline (no real growth)
307
318
327
342
350
February 1991 Budget Document 1
299
295
292
287
289
Cumulative Real Cut from
Baseline (percent)
2.6
7.2
10.7
16.1
17.4
Annual Real Cuts (percent)
2.6
4.6
3.5
5.4
1.3
1
Excludes effects of Desert Shield and Desert Storm.
Source: Budget of the United States Government, Fiscal Year 1992, Part Two, 184.
FEDERAL RESERVE BANK OF ATLANTA
35
Table 2
Defense-Related Employment by Census Region and State
(thousands)
Region
NORTHEAST
New England
Connecticut
Maine
Massachusetts
New Hampshire
Rhode Island
Vermont
Total New England
Middle Atlantic
New Jersey
New York
Pennsylvania
Total Middle Atlantic
1988 Active
Duty1
1988 D O D
Civilian
Private
Sector2
455.0
6,697
84.6
236.4
97.3
128.3
284.1
156.0
3,824
8,168
5,471
97.1
418.3
568.4
17,463
1.8
2.4
810.2
1,023.4
24,160
3.4
42.1
54.3
47.2
127.9
24.5
101.0
5,414
2,658
4,198
5,002
2,460
0.8
15.0
11.9
33.3
3.3
84.5
296.0
1.5
14.9
36.0
59.1
147.4
0.6
33.8
25.1
19.4
52.6
TOTAL NORTHEAST
82.3
130.9
NORTH CENTRAL
East North Central
Illinois
Indiana
Michigan
Ohio
Wisconsin
37.9
5.8
8.9
11.5
0.9
21.0
16.8
75.1
68.0
172.7
28.7
445.5
19,732
16.8
1,433
Total East North Central
65.0
West North Central
Iowa
Kansas
Minnesota
Missouri
Nebraska
North Dakota
South Dakota
0.4
23.2
0.9
15.2
13.1
10.9
6.7
20.1
70.4
38.8
269.8
10.1
379.0
135.4
123.3
565.8
1.8
5.5
33.6
145.2
76.3
Total West North Central
TOTAL NORTH CENTRAL
SOUTH
South Atlantic
Delaware
District of Columbia
Florida
Georgia
4.6
12.6
77.0
62.1
7.9
2.9
7.0
391.9
0.1
29.3
214.3
12.4
11.3
3.1
6.1
53.0
Private-Sector DefenseRelated as a Percentage
of Total Employment3
1,687
575
3,052
583
509
291
5.0
10.7
11.7
1.5
4.3
28.3
Total 1988
Employment
146.4
33.0
234.7
17.8
19.3
3.8
134.0
7.4
5.5
8.7
3.9
3.7
18.6
Total
Defense-Related
Employment
6.8
3.0
4.0
1.9
1.5
17.0
32.0
37.8
6.2
4.3
1.9
66.0
63.0
182.7
23.3
17.1
1,221
2,233
2,446
790
316
343
2.1
2.2
1.1
5.9
2.2
2.9
2.0
1.1
2.6
1.0
1.5
1.0
2.9
2.6
6.0
0.8
1.4
8,782
0.6
3.1
824.5
28,514
2.0
11.9
63.2
254.2
176.2
338
316
5,777
2,970
1.6
10.6
2.5
2.6
Maryland
North Carolina
South Carolina
Virginia
West Virginia
Total South Atlantic
East South Central
Alabama
Kentucky
Mississippi
Tennessee
Total East South Central
West South Central
Arkansas
Louisiana
Oklahoma
Texas
34.3
89.9
41.8
42.0
15.6
20.3
100.8
106.2
1.7
423.5
117.2
30.0
13.9
203.3
2.7
193.5
135.5
76.0
410.3
4.8
274.4
2,342
3,199
1,586
2,980
665
0.4
627.7
1,325.6
20,173
3.1
20.6
38.4
14.4
25.6
13.5
42.4
1,738
1,578
1,045
2,203
2.4
0.7
4.4
1.3
0.4
10.0
83.4
9.1
22.8
34.0
126.4
5.0
0.9
0.9
6.8
11.1
7.6
45.8
28.3
88.6
63.1
71.3
45.9
57.8
127.7
268.9
6,564
1.9
19.6
34.3
1,024
1,707
1,421
7,744
1.9
2.0
246.5
33.7
66.2
74.0
435.2
11.2
192.3
5.0
9.1
23.8
62.3
100.2
316.6
609.1
11,896
2.7
699.2
432.4
1,072.0
2,203.6
38,633
WEST
Mountain
Arizona
Colorado
Idaho
Montana
Nevada
New Mexico
Utah
Wyoming
2.8
24.8
38.3
5.6
4.2
9.2
15.2
5.8
3.9
10.4
13.7
1.3
1.3
2.0
108.9
117.3
8.4
7.5
16.3
40.9
51.6
Total Mountain
107.0
61.6
73.7
65.3
1.5
2.0
5.1
15.7
24.1
1.7
189.1
6.8
357.7
1,556
1,598
451
375
554
634
722
223
6,113
Pacific
Alaska
California
Hawaii
Oregon
Washington
22.5
204.8
44.8
0.7
42.0
Total Pacific
5.0
131.2
20.6
3.2
28.7
13.0
657.9
13.5
7.6
70.7
314.0
40.5
993.9
78.1
11.5
141.4
227
13,385
502
1,343
2,172
188.7
762.7
1,265.4
17,629
3.3
4.3
421.0
250.3
951.8
1,623.1
23,742
4.0
1,337.9
936.9
3,399.8
5,674.6
115,049
3.0
Total West South Central
TOTAL SOUTH
TOTAL WEST
TOTAL UNITED STATES
1
10.0
21.7
1.2
16.2
1.1
3.2
4.7
4.1
0.3
0.5
0.9
2.5
3.3
0.8
3.1
5.7
4.9
2.7
0.6
Data for 1988 are the latest for which all series necessary for estimating private-sector defense-related employment are available.
Based on the average value of prime contract awards during 1986-88.
Percentages are based on the actual numbers, not the rounded numbers shown.
Sources: Data for columns 1-4 are from U.S. Department of Defense, Directorate for Information Operations and Reports, Atlas/Data Abstract for United States and Selected Areas, Fiscal
Year 1988, Office of the Secretary of Defense Washington Headquarters Services. For column 5, data are from U.S. Department of Labor, Bureau of Labor Statistics, Employment
and Earnings, May 1990. Column 6 percentages were calculated by the Federal Reserve Bank of Atlanta.
2
3
Table 3
Potential Absorption of Displaced Private-Sector Defense-Related Workers
by Census Region and State
Region
NORTHEAST
New England
Connecticut
Maine
Massachusetts
New Hampshire
Rhode Island
Vermont
Total New England
Middle Atlantic
New Jersey
New York
Pennsylvania
Total Middle Atlantic
TOTAL NORTHEAST
N O R T H CENTRAL
East North Central
Illinois
Indiana
Michigan
Ohio
Wisconsin
Total East North Central
West North Central
Iowa
Kansas
Minnesota
Missouri
Nebraska
North Dakota
South Dakota
Total West North Central
TOTAL N O R T H CENTRAL
SOUTH
South Atlantic
Delaware
District of Columbia
Number of Employees
Displaced by
3 Percent Cut
(thousands)
Number of Employees
Displaced by
6 Percent Cut
(thousands)
Change in Annual
Average Total Employment
1988-89'
(thousands)
4.0
8.0
10
0.1
6.4
0.4
0.3
1.0
12.9
0.7
0.7
16
Absorption Rate 1989 2
3 Percent Cut
2.5
31.8
6 Percent Cut
1.2
15.9
0.2
0.1
7
-5
5
18.9
0.0
53.6
34
2.9
26.8
1.4
2
71
122
0.8
10.0
1
9.4
0.0
0.1
0.2
23.5
2.5
7.1
2.9
12.6
5.1
14.2
5.8
41.8
0.4
5.0
20.9
25.1
195
15.5
7.8
24.3
48.6
229
9.4
4.7
1.3
2.5
3.3
242
87
68
117
37
95.9
26.7
24.0
15.2
25.2
16.8
11.8
8.9
17.8
551
191.8
53.5
48.0
30.5
50.3
62.1
0.4
0.1
15
33.6
1.1
1.8
2.2
1.6
1.4
3.8
0.7
2.8
7.7
1.5
11
10.2
4.5
5.7
31.0
5.1
2.3
2.8
0.0
3.9
25.7
0.2
0.1
0.4
0.3
8.1
16.2
8
25
-3
1
3
60
17.0
34.0
611
36.0
18.0
0.2
0.3
2.0
11
66.4
33.2
-17
0.0
0.0
4.4
0.1
1.0
3.5
8.8
0.1
0.0
7.8
51.5
7.4
3.7
Florida
Georgia
Maryland
North Carolina
South Carolina
Virginia
West Virginia
Total South Atlantic
East South Central
Alabama
Kentucky
Mississippi
Tennessee
Total East South Central
West South Central
Arkansas
Louisiana
Oklahoma
Texas
Total West South Central
TOTAL SOUTH
WEST
Mountain
Arizona
Colorado
Idaho
Montana
Nevada
New Mexico
Utah
Wyoming
Total Mountain
Pacific
Alaska
California
Hawaii
Oregon
Washington
Total Pacific
TOTAL WEST
TOTAL UNITED STATES
1
4.4
2.3
3.5
0.9
0.4
6.1
0.1
8.7
4.6
7.0
1.8
0.8
12.2
0.2
18.8
68
48
88
73
29
42
36
15.6
21.0
25.0
81.0
69.3
6.9
442.5
7.8
10.5
12.5
40.5
34.7
3.4
221.2
37.7
378
20.1
10.0
1.3
0.3
1.4
0.8
2.5
0.7
2.7
1.7
3.8
35
56
30
44
27.5
166.0
21.8
51.8
13.7
83.0
10.9
25.9
7.7
165
43.0
21.5
0.6
1.0
0.5
7.4
1.2
2.1
1.0
14.9
9.5
29
42
17
116
49.2
40.8
34.9
15.7
24.6
20.4
17.5
7.8
19.0
204
21.5
10.7
32.2
64.3
747
23.2
11.6
2.2
2.0
0.0
0.1
0.2
0.5
0.7
0.1
4.4
3.9
0.1
0.1
0.3
0.9
1.4
0.1
5.7
11.3
62
-1
13
6
18
18
30
1
28.1
0.0
293.2
99.1
118.8
38.2
41.5
19.9
14.0
0.0
146.6
49.5
59.4
19.1
20.7
9.9
147
25.9
13.0
0.4
19.7
0.4
0.2
2.1
0.8
39.5
0.8
0.5
4.2
22.9
9
396
10
48
128
23.1
20.1
24.7
209.8
60.4
11.5
10.0
12.3
104.9
30.2
45.8
591
25.8
12.9
28.5
57.1
738
25.8
12.9
102.0
204.0
2,325
22.8
11.4
Changes are based on the actual numbers.
The number of times displaced defense workers could have been absorbed, given 1988-89 employment growth.
Source: Calculated by the Federal Reserve Bank of Atlanta from data in previous tables.
2
Table 4
Direct Defense Expenditures in 1989,
by Region and Major Expenditure Category1
(percent of total direct expenditures)
Radio, TV, and
Communications
Equipment
Aircraft
and
Parts
Ordnance
and
Accessories
Business
Services
Other
Transportation
Equipment
Northeast
28.90
17.08
7.06
13.10
5.78
.60
North Central
13.62
22.24
14.21
7.14
.94
3.56
South
17.65
12.32
5.92
18.23
9.66
9.48
West
19.01
14.86
26.88
11.72
3.17
5.45
United States
19.90
15.87
14.32
13.12
5.23
5.21
Region
New
Construction
1
Based on prime contract awards.
Source: Department of Defense Projected Defense Purchases: Detail by Industry and State, Calendar Years 1989-1994,
Directorate for Information Operations and Reports, November 1989.
Table 5
Direct Defense Expenditures in 1989,
by Selected States and Major Expenditure Category1
(percent of total direct expenditures)
State
Radio, TV, and
Communications
Equipment
Aircraft
and
Parts
Ordnance
and
Accessories
Business
Services
36.31
Other
Transportation
Equipment
New
Construction
23.35
4.26
Virginia
17.55
Colorado
20.80
5.65
18.13
20.69
Massachusetts
33.75
11.33
9.19
20.24
Missouri
11.91
45.12
19.83
5.42
6.94
44.79
3.69
8.27
18.49
19.90
15.87
14.32
13.12
5.23
Connecticut
United States
1
11.79
3.47
5.21
Based on prime contract awards.
Source: Department of Defense Projected Defense Purchases: Detail by Industry and State, Calendar Years 1989-1994,
Directorate for Information Operations and Reports, November 1989.
40
E C O N O M I C REVIEW, »MARCH/APRIL 1991
defense dollars and, therefore, most likely to have
a difficult time absorbing workers displaced by defense budget cuts.
effect nationally, and additional base closings remain too speculative at this point to assess their impact. In addition, the Defense Department asserts
that normal attrition and curtailed recruitment could
be used to accomplish as much as a 10 percent reduction in active duty military and direct civilian
employment during the next three to five years.
Conclusion
The recently released 1992 budget for the United
States proposes defense outlay cuts ranging from 3
to 6 percent in real terms over the next five years.
Congress and the Bush administration generally
agree that cuts in defense spending are appropriate
and desirable, given the size of the country's budget
deficits and the reduced threat of a conflict with the
Soviet Union. Desert Shield and Desert Storm are
not accounted for in the 1992 budget, and the impact the Gulf crisis may have on future defense cuts
is uncertain at this point. However, given the quick
resolution in the Gulf crisis, plans to cut defense expenditures are likely to move forward. In terms of
employment, defense outlay cuts in the range expected generally will not result in significant initial
adverse effects for the nation as a whole or for most
regions and states.
Base closings as well as the overall cuts in defense spending will affect active duty military and
Department of Defense civilian workers. The closings announced in 1988 will have only a marginal
Prime contract awards by the Department of Defense are good indicators of private-sector employment directly related to defense expenditures. On
the basis of these awards, employment likely to be
affected by the budget cuts can be identified by industry within a state or census region. Absorption
rates indicate that most areas have enjoyed sufficient
economic growth to absorb potentially displaced
private-sector defense workers back into the work
force in a reasonable fashion. The Northeast census
region proved to be the exception.
Five states—Virginia, Colorado, Massachusetts,
Connecticut, and Missouri—will potentially be hardest hit by defense cuts. These states have been generally more dependent on defense spending, and
they also showed less employment growth than
other states in the fairly representative year of 1989.
Of course, movement of these workers to places offering more new jobs may mitigate their difficulties
in getting other work, but out-migration in these
hard-hit areas may worsen the consequences for local communities.
Notes
1. For a thorough discussion and a model of these relationships, see Brian Coshell, "Defense Spending Cuts:
Implications for Deficit Reduction and the Economy,"
Congressional Research Service, Library of Congress,
January 5, 1990; and Mark A. Wynne, "The Long-Run
Effects of a Permanent Change in Defense Purchases,"
Federal Reserve Bank of Dallas Economic Review (January 1991): 1-16.
4. Much of the data and methodology for approaching
this issue was obtained from a report by Joseph V.
Cartwright titled "Potential Defense Work Force Dislocations and U.S. Defense Budget Cuts: An Illustration,"
prepared as a staff paper for the Department of Defense
in March 1990. This study also discusses the merits of
using prime contract awards to allocate direct privatesector defense-related employment.
2. Expenditures related to operations Desert Shield and
Desert Storm are excluded from both the 1990 actual
and 1991 estimated defense outlays in the 1992 budget.
An assessment of these expenditures' size or potential
impact is beyond the scope of this article.
5. This estimate is from the U.S. Department of Defense
Directorate for Information Operations and Reports, Selected Manpower Statistics, Fiscal Year 1988.
6. For a more detailed discussion of the impact of defense cuts by industry and occupation see Norman C.
Saunders, "Defense Spending in the 1990s: The Effect
o f D e e p e r Cuts," Monthly Lahor Review ( O c t o b e r
1990): 3-15.
3. Data for 1988 are the latest for which all series necessary for estimating the third category of defense-related
employment—private-sector workers—are available.
FEDERAL RESERVE BANK O F ATLANTA
41
Book Review
The Interstate Banking Revolution:
Benefits, Risks, and Tradeoffs for Bankers and Consumers
by Peter S. Rose.
Westport, Conn.: Greenwood Press Inc., 1989.
230 pages. $45.00.
he character of U.S. banking has changed
dramatically since the early 1980s as interstate banking has mushroomed. During
the 1981-90 period more mergers and acquisitions have occurred in banking and finance—on
average, more than 300 a year—than in any other industry. Until the early 1980s the McFadden Act and
the Douglas Amendment had effectively closed the
door to interstate banking, but banks had exploited a
number of regulatory loopholes to cross state lines.
Several bank holding companies moved to acquire
nonbank businesses—including finance companies,
mortgage banks, leasing firms, and the like—in the
1960s and 1970s. Before the Competitive Equality in
Banking Act of 1987 effectively prohibited the establishment of new nonbank banks, some banks sought
to avoid geographic restrictions by acquiring such
firms, which could perform only some of the functions
of a full-service bank. Finally, many banks crossed
state lines by acquiring troubled thrift institutions.1
T
During the past decade, however, full-service offices have become the dominant mode of interstate
banking as more and more states have enacted laws
allowing entry from other states (B. Frank King,
Sheila L. Tschinkel, and David D. Whitehead 1989).
By the end of 1988 more than half of the 14,600 interstate bank offices were permitted to offer all
banking services.
The ready availability of data on bank mergers
has encouraged research on diverse issues. In The
Interstate Banking Revolution: Benefits, Risks and
Tradeoffs for Bankers and Consumers, Peter S. Rose
examines the evidence, chiefly through a literature
survey, in three major research areas: the motives
underlying interstate banking; the potential benefits
and costs of interstate banking to banks, shareholders, and the public; and the track record of and public policy issues arising from the interstate banking
movement. The author, w h o holds the Jeanne and
42
John Blocker Chair of Business Administration in the
Department of Finance at Texas A&M University,
supplements his discussion of the literature with
anecdotes drawn from conversations with bankers.
The book's main contribution is the valuable insights it provides into the strengths and weaknesses
characterizing studies of the motives behind and the
public policy issues raised by interstate bank mergers. Its largest flaw is its lack of any discussion of
capital adequacy and deposit insurance reform and
how these issues may be expected to affect interstate
banking.
Motives for Bank Mergers
One way to gain insight into the different implications of bank mergers for the acquirer's and target's
shareholders and for social welfare is to analyze the
motives for mergers. Rose devotes an entire chapter
to discussing some of the economic, technological,
and legislative incentives for interstate banking.
Economic considerations commonly cited include
banks' efforts to attract capital to struggling local
economies, to broaden their pool of management
talent, to profit from improved stock prices for target
banks, and to restore a customer base suffering from
the departure of large business clients. Technological advances, too, which have reportedly led to
economies of scale and scope at financial institutions, may have motivated bankers to seek out new
markets and services.
Legislative developments that have hastened interstate banking include changes to help stem the rising
number of savings and loan failures and to promote
regulatory equity between bank and nonbank firms.
The failure to liberalize banks' service powers may
also have been an important underlying factor moti-
E C O N O M I C REVIEW, MARCH/APRIL 1991
vating interstate banking. Rose mentions that a more
liberal antitrust environment may have facilitated interstate banking. However, because antitrust laws
have a direct effect only on concentration in local
banking markets, it is unlikely that they have made
much difference to interstate banking, which generally has more influence on national or regional
banking concentration.2
To determine whether empirical support exists for
these explanations, the author examines the literature on bank merger motivation. Most of these studies are based on the premise that profitability, gains
in efficiency, diversification, and possible reductions
in risk should play important roles in shaping bank
mergers and acquisitions.
Achieving economies of scale is a powerful economic motive for bank mergers. In addition, banks
may hope to establish scope economies—the reduction in costs from providing an array of services—
through mergers. The author concludes that the
optimal bank size for achieving scale economies is
around $100 million in total assets and that cost savings are not a key consideration. Rose bases his
conclusion, however, on cost studies that used Functional Cost Analysis (FCA) data, which provide little
information about large banks' cost structures.3 A
large proportion of the dollar v o l u m e of interstate transactions involves banks with total assets
greater than $1 billion, for which FCA data are
nonexistent. 4
Researchers have more recently examined economies of scale at large banks using the intermediation
approach, defining output in terms of dollars (for example, William C. Hunter and Stephen G. Timme
1991 and Sherrill Shaffer and Edmond David 1986).
These studies point to economies of scale for banks
with u p to $5 billion in assets. Shaffer and David
suggest that, although these scale economies may
be statistically small, they are quite important economically. Thus, contrary to Rose's findings, scale
economies appear to be a valid motive for bank
mergers. Further, Rose fails to mention that existing
cost studies do not control for several factors typically associated with large bank mergers—such as
greater convenience, a wider array of services, lower
service fees, and a wider pool of skilled management. These scale economies can benefit both the
public and shareholders.5
The search for greater market power is a second important factor driving banks to cross state lines. Banks
expand geographically into less-than-competitive markets to generate higher profits. Interest in interstate
banking's effect on local banking market concentration
arises because of the apparent relationship between
market concentration and competition and this
FEDERAL RESERVE BANK OF ATLANTA
relationship's impact on shareholders and the
public. 6 Although banks' shareholders can benefit if a
less competitive environment translates into higher
profits or reduced risk, consumers and small businesses may ultimately pay higher prices for bank services.
The market power explanation for bank mergers
has several problems that Rose neglects to mention.
First, if one assumes that expanding market power
raises profits for some banks, this factor should be
reflected in the purchase price for target banks. Second, though the evidence appears to indicate a link
between structure and performance, there is also
some support for the alternative "efficient market
structure" hypothesis proposed by Michael Smirlock
(1985) and Douglas D. Evanoff and Diana L. Fortier
(1988). They argue that a positive correlation between market concentration and profits is merely the
result of a large efficiency gap among different
banks in the same market. Finally, the rather narrow
view of banking Rose adopts in his discussion of antitrust issues does not take into account the fact that
nonbank firms dilute market concentration by providing many of the same products banks offer. In
other words, banking concentration may overstate
actual product market concentration.
Overall, the evidence regarding bank market
structure issues is inconclusive. Rose is quick to
point out that the mixed evidence in this area may
be partly the result of methodological and data limitations of the studies.
Aside from motivations associated with economies
of scale and market power, a third reason banks
may seek mergers is to diversify earnings, both geographically and by customer type. Such diversification can reduce the overall credit risk of a bank's
asset portfolio. The acquirer may also broaden its
base of core deposits, which are more stable than
purchased funds. Shareholders can benefit from both
types of diversification. Hunter and Larry D. Wall
(1989) argue that whether the public benefits is debatable. Although banks with larger core deposits
may gain more stability, they may do so at the expense of market discipline resulting from depositors'
tendency to withdraw purchased funds when a bank
encounters financial problems.
Rose points out that regional banking compacts
limit gains from diversification because the economic
characteristics of neighboring states are similar to an
interstate bank's home state. However, banks increasingly have participated in loan syndications originated by institutions based outside their regions. In
addition, banks are more and more selling off many
of their loans into mortgage- and other asset-backed
securities. These trends undermine the argument that
asset diversification is a driving force behind mergers.
43
To gain additional insights into the motives
underlying bank mergers, Rose surveys studies
of a c q u i r i n g a n d a c q u i r e d b a n k s ' p r e m e r g e r
characteristics. He concludes that interstate bank
mergers have been motivated by an effort to produce and deliver retail banking services, implying
that mergers are undertaken partly to protect and increase the deposit base.
Evidence regarding profitability of mergers is
mixed, however. For example, Rose cites two of his
own earlier studies that suggest earnings and efficiency problems and somewhat greater risk exposure among both interstate acquirers and the banks
they purchased. In contrast, Hunter and Wall
(1989), analyzing the characteristics of a sample of
559 target banks during the 1981-86 period, report
that the most valued merger targets exhibited higher profitability and faster premerger growth in core
deposits, had higher ratios of loans to earning assets, and used more financial leverage.
Which Markets to Enter and
Which Banks to Target?
Rose also addresses the questions of how banks
assess the desirability of states for future entry and
how they select targets for acquisition. He studies
bank entry at the state level and concludes that interstate banking acquisitions have not spread randomly
or uniformly across the country but have been concentrated in selected states and regions. The principal factors driving bank expansion at the state level
are market size; growth rates of personal income,
population, and deposits; total deposits; and number
of banking offices per capita. Analyzing the attractiveness of individual states is of limited use, however, because it obscures differences across markets
within a state.
Recent research supports this conclusion. Using
the local market as the unit of observation, Dean F.
Amel (1989) examines the characteristics of banking
markets that have been attractive to entry by merger.
Amel finds that urban markets are five times more
likely to experience entry than are rural areas. Furthermore, high market profitability is very important
in rural areas, whereas low market concentration is
more critical in urban areas.
In addition to assessing the desirability of state
and local markets for entry, acquiring banks also
scrutinize target banks according to various criteria.
Rose suggests that the key factors underlying the
choice of target banks are earnings per share, the
stock-price-to-earnings ratio, and the merger premi-
44
um. However, he does not discuss the economic determinants of the purchase price. Hunter and Wall
(1989) found that target banks likely to attract the
highest purchase prices have high core deposit
growth and offer greater potential for diversifying
the acquirer's risk. This finding appears to support
Rose's conclusion that interstate banks have tended
to pursue acquisitions with a strong retail banking
orientation.
Effects of Mergers on Shareholders and
the Public
Shareholders of both acquiring and acquired interstate banks may benefit from mergers, Rose finds, especially in large merger transactions. His conclusion
is based mainly on studies by Sankar De and Marcia
Millon Cornett (1988) and Jack W. Trifts and Kevin P.
Scanlon (1987). More recent studies, though, suggest
that bank acquisitions are undertaken for reasons
other than to maximize shareholder value. David M.
Dubofsky and Donald R. Fraser (1989) found that, on
average, stockholders of acquiring banks did not
gain. Moreover, with the increase in the number of
potential bidders after 1981, Dubofsky and Fraser
note that managers placed greater value on the asset
size of the firm than on stockholders' wealth.
Interstate banking's impact on the public is more
difficult to assess. In the studies he surveys Rose finds
no evidence that interstate banking diminishes competition in local markets or raises the prices of financial services. In fact, he suggests that the retail
orientation of most interstate acquisitions may have
increased competition, especially in those communities with large numbers of households and small
businesses. Moreover, he discovers no support for
the hypothesis that interstate acquirers drain funds
away from local communities.
O n the other hand, Rose finds no undisputed evidence that interstate banking enhances economic
growth, increases bank profitability, or reduces the
risk of bank failure. Overall, he concludes, the "expected benefits from full-service interstate banking
will probably remain small or nonexistent for most
American communities for the foreseeable future."
Implications for Public Policy
Interstate banking raises some major public policy issues. One that Rose addresses is the probable
increase in regional and national banking concentra-
ECONOMIC REVIEW, »MARCH/APRIL 1991
tion. Rose emphasizes that, even if the number of
banks declined sharply, the system would remain
competitive as long as enough institutions compete
in local banking markets. However, regional banking concentration could diminish competition in the
financial services market for middle-market companies—those with annual sales between $50 million
and $250 million. Large commercial banks supply
services to middle-market businesses over geographic areas that are typically bigger than local
banking markets but smaller than the nation. Constance R. Dunham (1986) terms these regional banking markets. In assessing the need to redefine
geographic banking markets in response to this concern, Rose cites evidence suggesting that expanding
the focus of competitive analysis to include regional
banking markets would restrict mergers between
large banks.
Another key interstate banking issue, which Rose
fails to emphasize, is the need for reform in the deposit insurance system. Interstate bank mergers
have increased the number of institutions that may
be deemed too big to fail, thereby increasing the
burden on the Federal Deposit Insurance Corporation (FDIC). In the long run, either the fees banks
pay for federal deposit insurance need to be scaled
1. The need to provide avenues of rescue for failing banks
and savings and loans prompted states such as Texas to
enact interstate banking legislation during the 1980s.
2. Even in those interstate bank mergers in which local
market concentration has been affected, the regulatory
authorities have not invoked the potential competition
doctrine.
3. The Federal Reserve's Functional Cost Analysis data set
provides the most comprehensive sample of banks for
which the number of loan and deposit accounts are
available. Bank involvement in the FCA program is voluntary, and many banks d o not participate. In particular,
the FCA sample has too few banks with assets in excess
of SI billion to estimate their cost function reliably.
4. See Goudreau and Wall (1990) for evidence on southeastern bank mergers.
to reflect institutions' riskiness or other measures
that introduce market discipline need to be implemented.
Conclusions
On balance, Rose's work is an important contribution to the literature on interstate banking. The book
provides a timely summary of current debate and
should be of interest to academicians, bankers, and
regulators, although it offers few original insights
and fails to consider several relevant studies and
concerns. The issues surrounding interstate banking
take on added importance with the recently released
Treasury proposal, which seeks to amend the McFadden Act and the Bank Holding Company Act to
allow interstate branch banking as well as interstate
bank acquisitions on a nationwide basis.
A r u n a Srinivasan
The reviewer is an economist in the financial
Atlanta Fed's research department.
section of the
5. Hunter and Wall (1989) suggest that mergers may be
motivated by a desire to become "too big to fail" or "too
large to be acquired." Shareholders can benefit from a
bank's becoming too big to fail; however, the publicmay suffer because of increased risk-bearing by the
FDIC. Both shareholders and the public may lose in
mergers motivated by a desire to become too large to be
acquired because these transactions may reduce the
banking system's overall efficiency.
6. Most market concentration studies use intrastate merger
data. However, the findings are relevant for interstate
mergers because even though the initial entry into a
state is a market extension merger, subsequent acquisitions may involve horizontal mergers and raise antitrust
questions.
References
Amel, Dean F. "An Empirical Investigation of Potential
Competition: Evidence from the Banking Industry." In
Bank Mergers: Current Issues and Perspectives, edited
by Benton E. G u p , 29-68. Boston: Kluwer Academic
Publishers, 1989.
Dubofsky, David M., and Donald R. Fraser. "Regulatory
Change and the Market for Bank Control." In Bank
Mergers: Current Issues and Perspectives, edited by Benton E. Gup, 29-68. Boston: Kluwer Academic Publishers, 1989.
De, Sankar, and Marcia Millon Cornett. "An Examination of
Stock Market Reactions to Interstate Bank Mergers." Unpublished paper, Southern Methodist University, 1988.
Dunham, Constance R. "Regional Banking Competition."
Federal Reserve Bank of Boston New England Economic Review (July/August 1986): 3-19-
FEDERAL RESERVE BANK O F ATLANTA
45
Evanoff, Douglas D., and Diana L. Fortier. "Re-Evaluation
of the Structure-Conduct-Performance Paradigm in
Banking." Journal
of Financial
Services Research 1
(1988): 277-94.
Goudreau, Robert G., and Larry D. Wall. "Southeastern Interstate Banking and Consolidation: 1984-89." Federal
Reserve Bank of Atlanta Economic Review 75 (November/December 1990): 32-54.
Hunter, William C., and Stephen G. Timme. "Technological Change in Large U.S. Commercial Banks." Journal of
Business 64 (July 1991): 206-45.
Hunter, William C., and Larry D. Wall. "Bank Merger Motivations: A Review of the Evidence and an Examination
of Key Target Bank Characteristics." Federal Reserve
Bank of Atlanta Economic Review 74 (September/October 1989): 2-19-
Federal Reserve Bank of Atlanta Economic Review 74
(May/June 1989): 32-51.
Shaffer, Sherrill, and Edmond David. "Economies of Superscale and Interstate Expansion." Federal Reserve Bank
of New York Research Paper No. 8612, November
1986.
Smirlock, Michael. "Evidence on the (Non)Relationship between Concentration a n d Profitability in Banking."
Journal
of Money, Credit, and Banking
Y7 (February
1985): 69-83Trifts, Jack W., and Kevin P. Scanlon. "Interstate Bank
Mergers: The Early Evidence." Journal of Financial Research 10 (1987): 305-11.
U.S. Department of the Treasury. "Modernizing the Financial System: Recommendations for Safer, More Competitive Banks." February 1991.
King, B. Frank, Sheila L. Tschinkel, and David D. Whitehead. "Interstate Banking Developments in the 1980s."
46
ECONOMIC REVIEW, MARCH/APRIL 1991
? S® ^
1
SVí S s y -
'••"' -í?
Sf -•J-;.»;'
s
s
¥<
II
In)
-'
*
i
• • • --.:•-.:-•-•• • - - * '••••• • ••••:.:• ' '
mmm
i».--,>y.-:
'
<
1
Wm '
&
•
•.
:, -•••• '
t - •••
-
•
éWWf
•
n
Economic
Review
Federal Reserve Bank of Atlanta
104 Marietta St, N.W.
Atlanta, Georgia 30303-2713
Address Correction Requested
B u l k Rate
U.S. Postage
PAID
Atlanta, GA
P e r m i t 292
@FedFRASER