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^ Economic
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1
FEDERAL RESERVE BANK OF ATLANTA
•
NOVEMBER/DECEMBER 1989
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Review
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ISSN 0 7 3 2 - 1 8 1 3
V O L U M E LXXIV, N O . 6, N O V E M B E R / D E C E M B E R 1989, E C O N O M I C R E V I E W
2
Interest-Rate Caps,
Collars, and Floors
Peter A Abken
26
Financial Asset Pricing Theory:
A Review of Recent Developments
Ellis W. Tallman
The author surveys recent theoretical and empirical developments concerning asset pricing and
its relevance to real economic phenomena.
F.Y.I.
U.S. and Foreign Direct Investment Patterns
42
William ). Kahley
58
Aruna Srinivasan
64
Using these interest-rate risk management
instruments, investors can both hedge against
uncertainties resulting from interest-rate risk and
speculate on interest-rate movements.
Book Review
Index for 1989
FEDERAL RESERVE BANK OF ATLANTA II
Bank Costs, Structure, and Performance
by James Kolari and Asghar Zardkoohi
Interest-Rate Caps,
Collars, and Floors
Peter A. Abken
As some of the newest interest-rate risk management instruments, caps, collars,
and floors are the subject of increasing attention
among both investors and
analysts. This article explains how such instruments are constructed, discusses
their credit risks, and presents a new approach for valuing caps, collars, and
floors subject to default risk.
2
ECONOMIC REVIEW, NOVEMBER/DECEMBER 1989
S
ince the late 1970s interest rates on all
types of fixed-income securities have
b e c o m e more volatile, spawning a variety of m e t h o d s to mitigate the costs associated with interest-rate fluctuations. Managing
interest-rate risk has b e c o m e big business a n d
an exceedingly complicated activity. O n e facet
of this type of risk m a n a g e m e n t involves buying
and selling "derivative" assets, which can b e
used to offset or h e d g e changes in asset or
liability values caused by interest-rate movements. As its n a m e implies, the value of a derivative asset d e p e n d s on the value of another
asset or assets.
Two types of derivative assets widely discussed in the financial press a n d in previous
Economic Review articles are options a n d futures contracts. 1 Another derivative asset that
has b e c o m e extremely popular is t h e interestrate swap. 2 This article examines a group of
instruments known as interest-rate caps, collars, a n d floors, which are medium- to long-term
agreements that have proven to b e highly useful
for hedging against interest-rate uncertainties.
In this regard, caps, collars, and floors can b e
thought of as insurance poi icies against adverse
movements in interest rates.
Like interest-rate swaps, to which these instruments are closely related, caps, collars, a n d
floors are designed to h e d g e cash flows over
time rather than on a single date. The discussion
below will show how caps, collars, a n d floors are
related to each other, as well as how they may b e
constructed from the most basic derivative asset, the option. The article also shows t h e ways
in which caps, collars, and floors are created in
practice, along with the different kinds of interm e d i a r i e s involved in t h e c a p market. 3 The
rationale for hedging is reviewed, as are examples of how caps, collars, and floors are used by
different financial institutions. The last section
of the article considers the credit risk associated with buying caps, collars, or floors a n d presents a new a p p r o a c h for d e t e r m i n i n g t h e
expected cost of default on these instruments.
The author
Atlanta
is an economist
Fed's Research
ser of Noonan,
cussions
cap
about
Astley,
in the financial
Department.
and
Pearce,
the cap market
section
He thanks
Inc., for helpful
and for providing
rates.
of
the
Igor A. Lamdata
dison
What Is an Interest-Rate Cap?
An interest-rate cap, sometimes called a ceiling, is a financial instrument that effectively
places a maximum a m o u n t on the interest paym e n t m a d e on floating-rate debt. Many businesses borrow funds through loans or b o n d s on
which t h e p e r i o d i c interest p a y m e n t varies
according to a prespecified short-term interest
rate. The most widely used rate in both the caps
a n d swaps markets is the London Interbank
Offered Rate (LIBOR), which is t h e rate offered
on Eurodollar d e p o s i t s of o n e international
bank held at another. 4 A typical example of
floating-rate borrowing might b e a firm taking
out a $20 million b a n k loan on which t h e interest
would b e paid every three months at 50 basis
points (hundredths of a percent) over LIBOR
prevailing at each payment date. Other shortterm rates that are used in conjunction with caps
include commercial bank certificate of d e p o s i t
(CD) rates, the prime interest rate, Treasury bill
rates, commercial p a p e r rates, a n d certain taxexempt interest rates.
D a t a on t h e size of t h e c a p m a r k e t are
sketchy. The International Swap Dealers Association (ISDA) conducted a survey of its members in March 1989, and 44 of the association's 97
m e m b e r s responded. Almost 90 percent of the
respondents reported participating in the markets for caps, collars, floors, a n d o p t i o n s on
swaps. As of year-end 1988, these m e m b e r s
alone held 7,521 caps, collars, a n d floors, with a
total notional principal of $290 billion. The
volume conducted through 1988 was reported
as having notional principal of $172 billion.
These figures inflate the size of the market considerably because they are not adjusted for
transactions a m o n g t h e dealers themselves,
such as the purchase or sale of caps or floors to
h e d g e existing positions in these instruments.
On the other hand, the survey did not cover the
entire market. Nonetheless, t h e figures probably still greatly overstate the size of the market,
net of interdealer transactions or positions. 5
The interest-rate swaps market is vastly larger at
o v e r $ l trillion.
Most s t u d i e s of caps concern a g r e e m e n t s
offered by commercial or investment banks to
borrowers seeking interest-rate protection.
These instruments are often tailored to a client's
II
FEDERAL RESERVE BANK OF ATLANTA
needs, and, particularly in the case of caps, may
b e marketable or negotiable. Caps, collars, and
floors can also b e manufactured out of basic
derivative assets: options or futures contracts,
or a combination of the two. The following discussion will define caps, collars, and floors in
terms of option contracts, which are the simplest type of derivative asset.
Call a n d Put Options. An option is a financial
contract with a fixed expiration date that offers
either a positive return (payoff) or nothing at
maturity, d e p e n d i n g on the value of the asset
underlying the option. At expiration, a call option gives the purchaser the right, but not the
obligation, to buy a fixed number of units of the
underlying asset if that asset's price exceeds a
level specified in the option contract. The seller
or "writer" of a call has the obligation to sell the
underlying asset at the specified exercise or
strike price if the call expires "in the money."
The payoff on a call need not actually involve
delivery of the underlying asset to the call buyer
b u t rather can b e settled by a cash payment. The
caps market, for example, uses cash settlement.
If the asset price finishes below the exercise
price, t h e call is said to expire " o u t of t h e
money."
Put options are analogous to calls. In this case,
though, the purchaser has the right to sell, rather
than buy, a fixed number of units of the underlying asset if the asset price is below the exercise
price. The options discussed in this article will
all b e "European" options, which can only b e
exercised on the expiration date, as o p p o s e d to
"American" options, which can b e exercised any
time before or at expiration. As will b e seen,
caps, floors, a n d collars are European-style
option-based instruments, and the European
interest-rate call option is the basic building
block for the interest-rate cap.
Options on d e b t instruments can b e confusing if it is unclear just what the option "price"
represents. For d e b t instruments, t h e strike
price is referred to as the strike level, reflecting
an interest rate. Recall that the price of a d e b t
instrument, such as a Treasury bill or CD, moves
inversely with its corresponding interest rate; as
the interest rate of a Treasury bill rises, its price
falls. Thus, a call on a Treasury bill rate is effectively a put on its price. (To keep the exposition
clear, all discussion will b e in terms of options
on interest rates. The strike price will b e re4
ferred to as the strike level.) A call with a strike
level of 8 percent (on an annual basis) on some
notional amount of principal is effectively a cap
on a floating-rate loan payment coinciding with
the expiration of this option. (The notional
amount of principal is a sum used as the basis
for the option payoff computation. Cap, collar,
and floor agreements d o not involve any exchange of principal.)
Assume the call's payment date, known as the
reset date, falls semiannually. If the interest rate
is less than 8 percent on the reset date, the call
expires worthless. If t h e interest rate exceeds
8 percent, the call pays off the difference between the actual interest rate and the strike
level times the notional principal, in turn multiplied by the fraction of a year that has elapsed
since purchase of t h e option. For example, if
7Cjaps, floors, and collars are Europe an-style option-based instruments,
and the European interest-rate call
option is the basic building block for
the interest-rate cap. "
the actual rate of interest six months later were
10 percent a n d if t h e notional principal were
$1 million, the payment received from the call
writer would b e 2 percent (the 10 percent
actual rate minus the 8 percent strike level)
x $ 1,000,000 x 180/360 = $ 10,000.
A put option on an interest payment works in
a similar way a n d is the foundation for t h e
interest-rate floor. The holder of a floating-rate
loan could protect against a loss in interest
income from the loan by buying an interest-rate
put. A fall in the interest rate below the strike
level of the put would result in a payoff from the
option, offsetting the interest income lost because of a lower interest payment on the loan.
An option writer is basically an insurer who
receives a premium payment from the option
buyer when an option is created (sold). In fact,
the option price is alternatively called the option premium. The same party can simultaneECONOMIC REVIEW, NOVEMBER/DECEMBER 1989
ously write and buy options, thus creating an
interest-rate collar. Before exploring this strategy further, o p t i o n pricing must b e reviewed
briefly.
Option Pricing. An option's price before expiration d e p e n d s on several variables, including the value of the underlying asset on which
the option is written, the risk-free rate of interest (usually a Treasury bill that matures at the
same time as the option), the time remaining
before expiration, the strike price or level, and
the volatility of the underlying asset price. 6 For
later reference, readers should know how an
option price changes in response to a change in
an underlying variable, all other variables remaining constant. A call price rises (falls) when
the underlying asset price, volatility, or time to
expiration increases (decreases). It falls (rises)
"A cap can... be perceived as a series
of interest-rate call options for successively more distant reset dates; a
floor is a similarly constructed series of
put options."
with an increase (decrease) in t h e exercise
price. A p u t price rises (falls) with an increase
(decrease) in the strike price or volatility. It falls
(rises) with an increase (decrease) in the underlying asset price or interest rate. Unlike a call
price, a put price is not unambiguously affected
by an increase in the time to expiration, but the
put price d e p e n d s at any time on how far in or
out of the money the put is.7
For an interest-rate call option, the higher the
strike level compared to the current interest
rate, the lower the option value. Choosing a high
strike level (out-of-the-money) call is less expensive than buying an at-the-money or in-themoney call. Similarly, a low strike level (outof-the-money) put is cheaper than o n e with a
higher strike level.
This relationship between an option's strike
level and its price (the amount the option is out
of the money) is analogous to a large deductible
FEDERAL RESERVE BANK OF ATLANTA
on an insurance policy. Such a policy is less
likely to pay off and is therefore less expensive.
Likewise, the cost of interest-rate "insurance"
can b e reduced by taking a large deductible—
that is, buying an out-of-the-money option—
and thereby protecting only against large, adverse interest-rate movements.
Creating an interest-rate collar is another
method for reducing the cost of interest-rate
insurance. The call-option p r e m i u m for an
interest-rate cap may b e partially or completely
offset by selling a p u t o p t i o n that sets an
interest-rate floor. For a floating-rate debt holder,
the effect of this dual purchase is to protect
against rate movements above the cap level
while simultaneously giving u p potential interest savings if the rate drops below the floor
level.
If the cap and floor levels of a collar are narrowed to the extent that they coincide at the
current floating interest rate—that is, both put
and call options are at the money—the resulting
collar is so tight that it is similar to a forward contract on an interest rate, which is a derivative
asset that locks in the current forward rate.
When the contract expires, the change in the
contract's value that has occurred since t h e
inception of the contract exactly offsets t h e
change in the interest payment due. A rise in the
floating-rate payment is matched by an equal
gain in the interest paid to the contract holder; a
fall in the floating-rate payment is balanced by
an equal loss on the forward contract. In effect, a
forward contract converts a floating-rate payment to a fixed-rate payment.
The discussion thus far has been about a
single payment, yet, as m e n t i o n e d earlier,
actual cap, collar, or floor agreements are designed to hedge a series of cash flows, not just
one. A cap can thus b e perceived as a series of
interest-rate call options for successively more
distant reset dates; a floor is a similarly constructed series of p u t options. Assume that an
interest payment on floating-rate d e b t falls d u e
in three months, at the next reset date. If the
interest rate on the reset d a t e exceeds the
strike level, the cap writer would make a payment to the cap buyer on a date to coincide with
the cap buyer's own payment date on the underlying floating-rate debt.
A collar that consists of a series of at-themoney call and put options is equivalent to an
II
interest-rate swap. Buying the cap and selling
the floor transforms floating-rate d e b t to fixedrate debt, whereas selling the cap and buying
the floor switches fixed-rate d e b t into floatingrate debt. A swap that is constructed out of cap
and floor agreements is ca11 ed a synthetic
swap.
Caps brokers and dealers will sometimes determine rates on floors by deriving the rate from
swap and cap rates, which come from instruments that are more actively traded than floors
and therefore more accurately reflect current
market values.
In practice, swaps are not usually p u t together
from cap and floor agreements. Caps and floors
are more readily tradable than swaps because
credit risk is one-sided; swaps carry a credit risk
that is two-sided in nature. Matching buyers and
sellers for swaps is therefore more involved
than for caps or floors. 8
Examples of some caps, collars, and floors
should help the reader understand their operation. As the foregoing single-payment-date discussion illustrates, creating these instruments
amounts to an exercise in option pricing. O n e
widely used option-pricing model, known as the
Black futures option model, is used in the following examples. 9 Robert Tompkins (1989) explains caps pricing in terms of Black's model,
and the examples that follow are loosely patterned on Tompkins' approach.
The chief virtue of the Black m o d e l is its simplicity and ease of use, even though it has a
serious internal inconsistency when used t o
value d e b t options: the assumption that the
short-term interest rate (that is, the Treasury bill
rate) is constant. Options on short-term interest
rates have value, though, only if those rates are
less than perfectly predictable. In the last section of this paper, a more complex model that
does not suffer from this shortcoming is used to
price options. 1 0
Eurodollar Futures a n d Forward LIBOR. In
order to give realistic yet simple examples of
caps, collars, and floors, this article assumes
that the reset dates coincide with the expiration
dates of Eurodollar futures contracts, which are
traded at the Chicago Mercantile Exchange
(CME) and the London International Financial
Futures Exchange (LIFFE). Purchase of a Eurodollar futures contract locks in the interest payment on a $ 1 million three-month time deposit
to b e m a d e upon expiration of the futures con6
tract. The interest rate on the deposit is threemonth LIBOR. On the other hand, the seller of a
Eurodollar futures contract is obligated to pay
the specified LIBOR-based interest payment
at expiration. 11
Eurodollar futures expire in a quarterly cycle
two London business days prior to the third
W e d n e s d a y of March, June, S e p t e m b e r , a n d
December. The Chicago Mercantile Exchange
currently offers contract expiration months extending four years, with only March and September contracts for the fourth year.12 The interest
rate implied by a Eurodollar futures price may
b e regarded as a forward interest rate, that is,
the three-month LIBOR expected by the market
to prevail at the expiration date for each contract. 13
The Black model uses the futures price for a
particular contract expiration month as an input
to determine the value of a European call and
put option on that contract. In the case of Eurodollar futures contracts, the add-on yield (100
minus the futures price) is plugged into Black's
formula. Another crucial variable is the volatil ity,
which is either estimated from the historical
volatility of the Eurodollar futures yield or obtained as an i m p l i e d volatility from traded
Eurodollar futures options. 1 4 Chart I shows the
recent behavior of both of these volatility measures. Again, higher volatility results in highercost call a n d p u t o p t i o n s a n d h e n c e more
expensive caps and floors.
Table I gives two-year cap, floor, and collar
prices on three-month LIBOR for two arbitrarily
chosen dates, June 19, 1989, and December 14,
1987, that give reset dates which coincide with
Eurodollar futures expiration dates. The first
date illustrates pricing during a relatively low
volatility period when t h e term structure of
LIBOR rates, as given by the "strip" of prices on
successively more distant contracts, was just
about flat. The market was predicting virtually
no change in short-term interest rates over this
two-year horizon. In panel A of Table 1, the contract expiration months are given along with the
forward rates or add-on yields for each futures
contract. The row labeled time to
expiration
shows the n u m b e r of days from the creation of
the cap, floor, or collar to the expiration date for
each contract. Another input into Black's formula, the risk-free rate, is taken to be the Treasury
bill or zero-coupon b o n d yield for which the
ECONOMIC REVIEW, NOVEMBER/DECEMBER 1989
volatility
in
Chart 1.
Implied and Historical Volatilities for Eurodollar Futures Prices
percent
50
(daily data, December
January 1986
Higher
volatility,
sive caps,
Note:
1985-July
1989)
- f
Gaps
shown
January 1987
such as that exhibited
in Charts
in Chart
2, 3, and
1 result
around
January 1988
the time of the October
1987 stock-market
January 1989
break,
results
in more
expen-
4.
from missing
observations.
Source: Chicago Mercantile Exchange.
expiration falls nearest t o the futures expiration date.
The first example prices a two-year 10 percent
cap, which consists of t h e sum of seven call
options. At 10 percent, this cap is clearly out of
the money. The c o m p u t e d call option price is
expressed in basis points. The calls b e c o m e
progressively more expensive as t h e time to
expiration increases, reflecting t h e rising t i m e
value of the calls. The shorter-maturity calls have
little value because they are out of the money
and, given the volatility, only a slight chance
exists that they might finish in the money. Although the more distant calls are also out of the
money, there is more t i m e (and more uncertainty) a b o u t what LIBOR will do. Thus, their
value is greater because of the higher probability that they might expire in t h e money. The
FEDERAL RESERVE BANK OF ATLANTA
sum of these calls is t h e cap rate, which is 147
basis points (rounded from I47.1).' 5 For a threemonth contract with a nominal face value of $ l million, a one-basis-point m o v e is worth $25
($l million x .01% x 90/360). Translated into dollars, 147.1 basis points is $3,677.60 (147.1 x $25),
which represents the dollar cost of placing a cap
for two years on a $1 million loan. This example
was c o m p u t e d ignoring t h e risk of default on the
cap. It also a s s u m e s that p a y m e n t s at reset
dates, if owed, are m a d e at t h e time of the
reset date.
Next, a slightly out-of-the-money 7.5 percent
floor is shown. The total cost is 96 basis points,
or $2,396.61. As m e n t i o n e d above, t h e cost of
interest-rate protection can b e r e d u c e d by
creating a collar, which is s o m e t i m e s referred to
as a ceiling-floor agreement. In this example,
II
Table 1.
Examples of Two-Year Cap, Floor, and Collar Prices on Three-Month LIBOR
Panel A: June 19,1989; Volatility, 18 percent
September December
1988
1988
March
1989
June
1989
September December
1989
1989
March
1990
91
9.02
8.46
182
8.84
8.47
273
8.64
8.54
364
8.71
8.56
455
8.77
8.59
546
8.87
8.59
637
8.86
8.56
Call prices
(10.0 percent strike)
5.3
10.3
12.9
19.9
26.5
34.1
38.1
Put prices
(7.5 percent strike)
.6
4.7
11.8
15.4
18.6
20.6
24.2
Time to expiration (days)
Forward rate
Risk-free rate
Zero-cost collar
10 percent cap implies
7.85 percent floor
7.5 percent floor
Cost in basis points: 96
Cost in dollars: $2,396.61
10 percent cap
Cost in basis points: 147
Cost in dollars: $3,677.60
Panel B: June 19,1989; Volatility, 18 percent
September December
1988
1988
March
1989
June
1989
September December
1989
1989
March
1990
Call prices
(11 percent strike)
.4
2.2
3.8
7.6
11.8
16.9
20.3
Put prices
(7 percent strike)
.1
1.3
4.7
7.2
9.5
11.2
13.9
Zero-cost collar
11 percent cap implies
7.19 percent floor
7 percent floor
Cost in basis points: 48
Cost in dollars: $1,198.08
11 percent cap
Cost in basis points: 63
Cost in dollars: $1,575.84
Panel C: December 14,1987; Volatility, 25 percent
March
1989
June
1989
September
1989
371
8.88
7.51
455
9.11
7.66
553
9.31
7.79
644
9.48
7.92
28.9
45.9
62.0
78.0
91.6
26.8
29.0
30.5
32.9
34.8
September December
1988
1988
March
1988
June
1988
91
8.09
6.09
182
8.34
6.79
280
8.62
7.11
Call prices
(10 percent strike)
2.1
12.5
Put prices
(7.5 percent strike)
16.2
23.0
Time to expiration (days)
Forward rate
Risk-free rate
10 percent cap
Cost in basis points: 321
Cost in dollars: $8,025.53
Note: Dollar
8
amount
is for $1,000,000
7.5 percent floor
Cost in basis points: 193
Cost in dollars: $4,829.68
in notional
Zero-cost collar
10 percent cap implies
8.05 percent floor
principal.
ECONOMIC REVIEW, NOVEMBER/DECEMBER 1989
selling a 7.5 percent floor would substantially
reduce t h e cost of a 10 percent cap. The combination would cost a b o u t 51 basis points, or
$1,281. However, by judiciously selecting the
floor level—in this case, 7.85 percent—the price
of the cap can b e driven to zero. 16 Marketing
p e o p l e d e l i g h t in explaining that d o w n s i d e
interest-rate protection (the cap) can b e obtained at no cost: just sell a floor. 17 Of course,
though, this strategy carries a cost. The holder of
an interest-rate collar has traded away potential
savings on interest-rate declines below the floor.
This caveat notwithstanding, a collar for which
the floor exactly matches the cap will b e referred to as a zero-cost collar.
Panel B illustrates how t h e cost of caps a n d
floors falls by selecting more out-of-the-money
levels. Increasing the cap by o n e percentage
point to 11 percent reduces t h e cap rate substantially to 63 basis points, or $1,575.84. Decreasing t h e floor by half a p e r c e n t a g e p o i n t t o
7 percent more than halves the cost to 48 basis
points, or $ 1,198.08. A zero-cost collar with an
11 percent cap effectively lowers the floor to 7.19
percent.
The final example, reflected in panel C of
Table 1, shows prices for caps, collars, a n d floors
during the relatively high volatility period after
the October 1987 stock market break. As depicted in Chart 1, Eurodollar futures' volatility surged
during a n d after t h e O c t o b e r 21 crash; t h e
degree of fluctuation had abated greatly by late
January, although it had not returned completely to precrash levels. The implied volatility
was 25 percent on D e c e m b e r 14, 1987, as compared to 18 percent on June 19, 1989, in the
earlier examples. The 10 percent cap priced in
panel C is substantially m o r e costly than the o n e
in p a n e l A. The cost is 321 basis points, or
$8,025.53. Another important factor contributing
to the higher cost is t h e rising structure of LIBOR
forward rates. Although t h e futures nearest to
expiration indicate a forward rate of 8.09 percent as compared to 9.02 percent in the June 19,
1989, example, t h e distant futures for December 14, 1987, have forward rates that are well
above those for June 19. The upward sloping
term structure of interest rates for D e c e m b e r 14
reinforces the effect of higher volatility on raising cap and floor rates. The floor is more expensive as well at 193 basis points, or $4,829.68.
Interestingly, the zero-cost collar with a 10 per-
cent cap is only slightly more constraining with a
floor of 8.05 percent as compared t o 7.85 percent in the previous example, which exhibited
low volatility and flat term structure. 18
Caps, Collars, and Floors in Practice
At first sight, creating caps, collars, a n d floors
would a p p e a r to b e a s i m p l e matter because
options are traded on the Eurodollar futures
contract. Selecting the appropriate strike levels
and expiration dates would a p p e a r to b e all o n e
n e e d s t o manufacture a cap, collar, or floor.
However, as m e n t i o n e d above, Eurodollar contracts extend into the future for at most four
years (which nevertheless is an unusually large
n u m b e r of m o n t h s for a futures contract). Eurodollar futures options traded at the Chicago
Mercantile Exchange currently have expiration
dates ranging out only two years, in a quarterly
cycle that matches that of the Eurodollar futures contracts. 19
Another limitation of Eurodollar futures options is that only contracts expiring within the
three months or so from t h e current d a t e are
liquid, that is, they are the only ones that are
actively traded so that their prices at any t i m e
reliably reflect equilibrium values. The options
also are limited to strike levels in increments of
25 basis points, whereas the futures have increments of o n e basis point. Unlike Eurodollar
futures and options, caps, collars, a n d floors
have b e e n created with maturities extending as
much as 10 years. Furthermore, actual caps,
collars, a n d floors can b e created on any day, not
just on futures and options expiration dates.
The actual use of futures and options t o fashion
caps, collars, and floors is neither a straightforward nor a riskless matter.
The solution to this p r o b l e m is t h e use of
existing futures a n d options contracts to create
the desired positions synthetically. Synthesizing an options position using options or futures
contracts—or a combination of the two—requires
not only taking appropriate positions in the
existing liquid contracts b u t also altering that
position over t i m e so that the value of t h e actual
position tracks or "replicates" t h e desired position. This process is known as dynamic
hedging.
Theoretically, the replicating portfolio of actual
II
FEDERAL RESERVE BANK OF ATLANTA
futures a n d options contracts can exactly match
the value of, say, a cap sold to a counterparty. 2 0
In reality, managing a replicating portfolio is a
risky and costly activity. 21 Tracking errors cumulate since costly trading cannot b e conducted
continuously as is theoretically required and
because mismatches can occur with t h e expiration dates and possibly also with t h e interest
rates involved. Using E u r o d o l l a r futures t o
h e d g e a cap b a s e d on the commercial p a p e r
rate exemplifies t h e latter. 22
The Over-the-Counter Market
In view of t h e c o m p l e x i t i e s a n d risks of
dynamic-hedging strategies, most cap, collar,
and floor users prefer over-the-counter instruments. Commercial a n d investment banks create these instruments themselves, possibly by
manufacturing them through dynamic hedging.
Nonfinancial users t e n d to rely on the expertise
of these financial institutions and are willing to
pay for t h e convenience of interest-rate risk
m a n a g e m e n t products issued through an intermediary. The intermediaries may also b e more
willing t o bear t h e risks associated with hedging
because of t h e scale of their operations. In fact,
Keith C. Brown and Donald J. Smith (1988) describe the increasing involvement of banks in
offering interest-rate risk m a n a g e m e n t instruments as t h e reintermediation of commercial
b a n k i n g . Since t h e 1970s, commercial b a n k s
have played less of a role in channeling funds
from lenders to borrowers. With the growth of
interest-rate risk m a n a g e m e n t , though, their
intermediary role is being restored, albeit in a
different form.
Commercial banks, particularly t h e largest
money-center banks, are better a b l e to absorb
a n d control t h e hedging risks associated with
managing a caps, collars, and floors portfolio,
and these institutions are better a b l e to evaluate t h e credit risks inherent in instruments
bought from other parties. Credit risk arises
b e c a u s e any counterparty selling a cap, for
example, is obligated to m a k e payments if the
cap moves in the money on a reset date. That
counterparty could go bankrupt at s o m e point
during t h e course of the cap agreement a n d
would default on its obligation. (This issue is
10
examined in detail in the last section of this article.) By taking positions in caps, collars, and
floors, commercial banks—and to a lesser extent, investment banks—act as dealers by buying a n d selling to any counterparties. Within
their portfolio or " b o o k " of caps a n d floors,
individual instruments partially net out, leaving
a residual exposed position that t h e banks then
h e d g e in the options a n d futures markets. Much
trading of caps, collars, a n d floors consists of
purchases a n d sales of these instruments t o
adjust positions a n d risk exposures, so much of
the caps market's v o l u m e is generated by interdealer transactions. In addition to t h e d o z e n or
so commercial a n d investment banks in New
York and London that d o m i n a t e t h e caps market, there are a b o u t half a d o z e n caps brokers,
who d o not take positions themselves b u t instead match buyer a n d seller. 23
Caps, collars, a n d floors are usually sold in
multiples of $5 million, b u t because of the cust o m i z e d nature of the over-the-counter market
other amounts can b e arranged. Most caps have
terms that range from o n e to five years and have
reset d a t e s or f r e q u e n c i e s that are usually
monthly, quarterly, or semiannual. Caps b a s e d
on three-month LIBOR are the most c o m m o n
and t h e most liquid or tradable. From the purchaser's point of view, buying a cap that matches
t h e characteristics of t h e liability being h e d g e d
might seem best. Even strike levels and notional principal amounts can b e chosen to vary
over the term of an agreement in a predeterm i n e d way, b u t good fit comes at a price. Transactions costs are higher for such tailored products, as reflected by the larger difference between b i d a n d offer rates on u n c o m m o n caps.
This wider spread also increases t h e cost of
removing caps by selling them before their term
expires. Many users o p t for a liquid cap a n d are
willing to a b s o r b t h e basis risk—the risk from a
mismatch of interest basis or other characteristics—in order t o avoid the higher cost of a less
liquid instrument.
Caps a n d floors are usually available at strike
levels within several percentage points of t h e
current interest-rate basis and are most commonly written out of the money. Settlement
dates typically occur after reset dates, u p o n
maturity of t h e underlying instrument. For exa m p l e , interest on a three-month Eurodollar
d e p o s i t is credited u p o n maturity of t h e deECONOMIC REVIEW, NOVEMBER/DECEMBER 1989
posit. A cap on three-month LIBOR would have
a three-month lag between a reset date and
actual settlement. Most payments for caps are
m a d e u p front, although they can also b e amortized. When a cap and a floating-rate loan c o m e
from the same institution, the two are usually
treated as a single instrument; thus, when the
floating rate exceeds the strike level, payment is
limited to the strike level and the cap does not
pay off directly. 24
Long-Term Caps. During the mid-1980s, early
in the development of the caps market, longerterm caps were created directly from floatingrate securities rather than synthetically. Two
kinds of floating-rate instruments were used:
floating-rate CDs and floating-rate notes. 2 5
Floating-rate notes are d e b t obligations usually
indexed to LIBOR, and floating-rate CDs are
medium-term deposit instruments that are also
typically indexed to LIBOR. The innovation that
sparked much activity in the caps market was
the issuance of capped floating-rate notes and
CDs that in turn had their caps stripped off and
sold as separate instruments sometimes known
as "free-standing" caps.
As an illustration, consider the floating-rate
CD. Banks use ordinary CDs as well as variablerate CDs to acquire funds for the purpose of
making loans and funding other balance-sheet
assets. The capped floating-rate CD was prom o t e d as a m e t h o d of raising funds below
LIBOR, the rate on an uncapped CD with a variable rate of interest. The reason is that, after
issuing a capped floating-rate CD to a depositor, a bank could then sell the corresponding
cap into the caps market and collect premium
income. Because CDs of this type typically fund
floating-rate loans, the bank would b e fully
h e d g e d after selling t h e cap. Funding costs
would b e lowered if the premium for the cap on
the floating-rate CD were less than the premium
t h a t t h e b a n k c o l l e c t e d u p o n selling the cap into
the market. 26 This method of creating or "sourcing" caps, floors, and collars—through capped
floating-rate CDs and floating-rate n o t e s became extremely popular b u t was short-lived.
Reportedly, the longer-term caps were gradually perceived to b e undervalued, such that
cap writers were not being compensated for the
risks of having to make payments to cap holders
if interest rates rose above strike levels. 27 Also
contributing to the demise of this method of
FEDERAL RESERVE BANK OF ATLANTA
sourcing was a flattening of the yield curve that
m a d e floating-rate borrowing less attractive and
reduced cap prices. Today, few caps, collars, or
floors are created beyond the five-year maturity.
Charts 2-4 give actual cap bid and offer rates,
in basis points, q u o t e d by o n e major caps
broker in New York. The bid rate is the rate at
which the broker is wil 1 ing to buy a cap; the offer
rate is the rate at which the broker sells a cap.
The spread between the two represents the
transactions costs of match ing buyer with seller.
Charts 2, 3, and 4, respectively, give the rates on
two-year 8 percent, three-year 10 percent, and
five-year 10 percent caps. These rates are just a
sample; many other strike levels are available.
The strike levels quoted change over time as
interest rates change. Cap strike levels that
move too far in the money or out of the money
are discontinued and replaced by caps with
strike levels that are in greater d e m a n d . All of
these series are highly correlated. They are also
correlated with the volatilities shown in Chart I,
which are a major determinant of cap values. 28
The Motivation for Hedging
and Some Hypothetical Examples
With some background on the caps, collars,
and floors market, the use of interest-rate risk
management instruments can now b e put into
perspective by briefly considering the nature of
hedging. Caps, collars, and floors are often
talked about in terms of an insurance analogy.
They are instruments that can b e used to hedge
assets orliabilitiesand thus protect against loss
resulting from interest-rate risk. In practice,
though, distinguishing between hedging and
speculating in interest-rate risk management is
s o m e t i m e s difficult, especially with optionbased instruments. Discretion is required in
selecting the timing of the hedge, the strike
level, and the maturity of the instrument, all of
which are usually predicated on some opinion
of what interest rates and other variables are
expected to do. Selling a cap or floor, for example, is a way to generate income on a fixedincome portfolio by collecting the premiums.
The decision to sell often reflects a difference of
opinion regarding the volatility implied by the
II
Chart 2.
Two-Year 8 Percent Cap Bid and Offer Rates
Rate in
basis points
400 T
(daily data, March 1987-October
1988)
300
100
I T
o J
March 1987
1
1
p
September 1987
March 1988
The spread
between
the bid and offer rates represents
the transactions
costs
Note:
in Charts
2, 3, and 4 reflect
rates were not
available.
Gaps
days for which
of matching
September 1988
buyer
and
seller.
Source: Noonan, Astley, and Pearce, Inc.
cap or floor. If a m o n e y manager thinks a cap is
overvalued because t h e market's expectation of
volatility is higher than his or her own, then selling an out-of-the-money c a p might b e a g o o d
move. If t h e m o n e y manager's j u d g m e n t a b o u t
volatility is correct, even small upward moves in
the interest rate may not w i p e out all of the prem i u m income. At t h e s a m e time, t h e sale provides a limited h e d g e against small downward
moves in rates, again because of t h e p r e m i u m
receipt.
Even determining the effect of hedging can
b e problematic, since a firm's purchase of a cap,
for example, to h e d g e t h e interest-rate risk of a
particular liability could increase t h e variability
of the firm's net worth. The financial claim b e i n g
h e d g e d may itself h e l p offset the variability of
another financial claim on t h e balance sheet.
12
The net result of a specific h e d g e could b e t o
increase the interest-rate risk exposure of the
firm.
A more fundamental issue is why firms h e d g e
in t h e first place. A basic insight derived from
t h e economics of uncertainty is that risk aversion leads individuals to prefer stable income
a n d c o n s u m p t i o n streams t o highly variable
ones. Given an assumption of risk aversion on
the part of decision makers, o n e can show that
their welfare or utility (that is, their economic
well-being) is greater over time if they enjoy
smooth income or c o n s u m p t i o n opportunities
rather than erratic ones. 2 9 Hedging is a way of
improving economic well-being by trading off
income or c o n s u m p t i o n in g o o d times for greater income or consumption in b a d times. Thus, a
hedging strategy serves a well-defined p u r p o s e
ECONOMIC REVIEW, NOVEMBER/DECEMBER 1989
Rate in
basis points
Chart 3.
Three-Year 10 Percent Cap Bid and Offer Rates
(daily data, March 1987-June
1989)
300
200
-
100
March 1987
The rates
Chart
depicted
September 1987
in Chart
3 are highly
March 1988
correlated
with
September 1988
those
in Charts
March 1989
2 and 4, as well as with
the volatilities
in
1.
Source: Noonan, Astley, and Pearce, Inc.
for risk-averse economic agents, such as farmers
or a firm's owner-manager. The issue is less
clear-cut for widely held corporations, which
actually are t h e typical users of interest-rate
risk-management tools. A corporation owned by
a large n u m b e r of stockholders n e e d not operate like a risk-averse decision maker because
each stockholder can insulate his or her wealth
and consumption opportunities from risk, specific t o t h e corporation's activities, by h o l d i n g
a diversified portfolio of assets.
Clifford W. Smith a n d R e n é M. Stulz ( 1985) surveyed managers of widely held, value-maximizing
corporations t o d e t e r m i n e t h e motivations behind hedging behavior. According to the researchers, managers engage in hedging of a
firm's value for three basic reasons. The first
explanation is tax-related; Smith and Stulz arFEDERAL RESERVE BANK OF ATLANTA
g u e that, on average, a less variable pretax firm
value implies a higher after-tax firm value than
d o e s a more variable pretax value. The reasoning turns on their assumption that t h e level of
corporate tax liabilities grows at an increasing
rate with rising pretax firm value because of t h e
progressive structure of the tax code. Hedging
helps reduce the variability of pretax firm value
a n d therefore raises after-tax value. Second,
Smith and Stulz maintain that hedging lowers
the probability that t h e firm will g o bankrupt
a n d thus incur bankruptcy costs. Hedging firm
value would benefit stockholders by reducing
the expected future costs of bankruptcy that
lower current firm value. A related p o i n t is that a
firm's d e b t may often contain covenants that
force the c o m p a n y to alter investment policies
that the shareholders would like to see underI3
Rate in
basis points
700 ^L
Chart 2.
Five-Year 10 Percent Cap Bid and Offer Rates
(daily data, March 1987-June
1989)
600
500-
400
300
200
100
September 1987
The longer
expiration
date on a five-year
cap results
March 1989
September 1988
March 1988
in prices
that are relatively
higher
than
those
on
shorter-term
caps.
Source: Noonan, Astley, and Pearce, Inc.
taken. Hedging reduces the likelihood of financial distress and the limitations on managers'
discretion that b o n d covenants may impose. A
third reason for hedging is that when managerial
compensation is tied to the firm's value, managers may become more risk-averse in order to
maintain that value.
Participants in the Caps, Collars, a n d Floors
M a r k e t While the precise social value of interestrate risk management products is not fully understood in the case of widely held corporations,
such products are clearly becoming increasingly
popular among corporate treasurers and other
financial managers. End users of caps, collars,
and floors typically include firms seeking to
limit exposure to adverse movements in shortterm interest rates, such as a firm that sells commercial paper to fund its purchases of inventory.
14
Specific market participants are depository institutions, particularly savings and loan associations (S&Ls) ; corporations going through leveraged buyouts (LBOs) or taking on d e b t to fend
off hostile takeovers; and real estate developers, who are often highly leveraged with
floating-rate debt. Unfortunately, the only information about these applications is anecdotal.
Also, compared to the potential market, the
actual market is probably very small. Many
potential users are unaware of or cautious about
interest-rate risk management instruments.
Any user of interest-rate swaps is potentially
also a user of caps, collars, and floors. Larry D.
Wall and John J. Pringle (1988) conducted a systematic search of annual reports for 4,000 firms
that used interest-rate swaps in 1986. The stocks
of these firms were traded on the New York
ECONOMIC REVIEW, NOVEMBER/DECEMBER 1989
Stock Exchange, the American Stock Exchange,
or t h e over-the-counter market. Of this sample,
250 firms were identified as swaps market participants. Over 50 percent of this group were
banks, savings a n d loans, a n d other financial
services firms; commercial banks alone accounted for half of these. In addition, Wall a n d Pringle
report that "the overwhelming majority of thrifts
(59 percent), manufacturing firms (69 percent),
a n d nonfinancial, n o n m a n u f a c t u r i n g firms (77
percent) are exclusively fixed-rate payers." 3 0 As
a conjecture, the profile of caps, collars, a n d
floor users may b e q u i t e similar to that for swaps
users. The fact that credit risks for caps and
floors are one-sided, however, suggests that
firms with weaker credit ratings probably use
caps and floors because they cannot gain access
to t h e swaps market on favorable terms.
Anecdotal accounts from various sources illustrate how different end users e m p l o y caps,
collars, or floors in their management of interestrate risk. Many savings a n d loans, for instance,
have b e e n active users of these option-based
instruments. The interest-rate risk confronting
S&Ls, a n d d e p o s i t o r y institutions generally,
may b e considered in terms of their net interest
margins, that is, the difference between t h e
rates at which an institution lends a n d borrows.
S&Ls are particularly vulnerable t o changes in
interest rates because maturities (or alternatively, the durations) of these institutions'
assets, p r e d o m i n a n t l y long-term mortgages,
greatly exceed t h e maturities of their liabilities,
most often short-term t i m e a n d savings deposits. Thus, a rise in rates raises t h e interest
expense on an S&L's short-term liabilities with
possibly little increase in interest earnings on
its mortgages. The net interest margin narrows
and could very well b e c o m e negative. O n e solution is to convert the floating-rate interest
expense on the liabilities into fixed-rate payments via an interest-rate swap. The net interest
margin would then b e c o m e much more stable.
However, a weak credit standing could m a k e
such a swap too expensive or unobtainable. A
cap on the floating-rate liabilities could b e an
effective alternative. An S&L's credit rating
would b e irrelevant to a cap writer, who bears no
credit exposure. 31
As another example, consider a commercial
bank's portfolio manager w h o is responsible for
overseeing a portfolio of floating-rate notes.
Suppose this manager believes that a large drop
in short-term interest rates, currently at a b o u t
8 percent, is a b o u t to occur. H e wants to protect
the portfolio's earnings and therefore buys an
out-of-the-money 7 percent interest-rate floor.
Concerned a b o u t the cost of this protection a n d
reasonably convinced that rates will not rise
substantially, he also decides to sell a 9 percent
interest-rate cap to create a collar on the portfolio. This e x a m p l e highlights t h e discretion
involved in selecting a hedge. A floor could have
b e e n in place all along, b u t maintaining a floor
reduces a portfol io's return by the a m o u n t of the
premium expense. Only when the manager has
strong concerns a b o u t a drop in rates is the
floor purchased.
As a final example, the corporate treasurer of
a consumer products firm is worried a b o u t t h e
prospects of a rise in interest rates because her
company has recently undergone a leveraged
buyout. The financing strategy for the LBO inc l u d e d heavy reliance on floating-rate d e b t
secured from a syndicate of commercial banks.
The firm's debt-to-equity ratio has soared, and
even a m o d e s t rise in rates could bankrupt the
company. After the LBO the firm's credit standing was downgraded by the rating services; consequently, access t o t h e swap market is effectively foreclosed. Buying a two-year interestrate cap to cover the firm's floating-rate exposure seems to b e a p r u d e n t action. 32 The
treasurer expects earnings will b e more robust
after a two-year interval. Also, the protection
gained for a relatively short-term horizon makes
sense b e c a u s e during this period t h e firm
would b e downsizing a n d reorganizing its operations.
Credit Risk
The earlier discussion of the over-the-counter
market for caps, collars, and floors a l l u d e d t o
t h e riskof default inherent in these instruments.
That risk is present because the seller of a cap or
floor is agreeing to fulfill a contract in the event
the cap or floor moves in t h e money on a paym e n t date. Since the seller is a firm, whether a
commercial bank, investment bank, or nonfinancial institution, its assets are limited, a n d
thus the company is exposed to t h e possibility
II
FEDERAL RESERVE BANK OF ATLANTA
of bankruptcy. The p r o b a b i l i t y of d e f a u l t is
rather small for t h e typical caps, collar, or floor
writer who also typically issues investment-grade
b o n d s into the market. Moody's Investors Service, o n e of the major b o n d rating firms, recently
released a study indicating that from 1970 t o
1988 t h e average annual rate of default by issuers of investment-grade b o n d s was 0.06 percent, as c o m p a r e d t o an average annual default
rate of 3.3 percent for j u n k b o n d issuers. 3 3
Because t h e consequences of default can b e
financially damaging, default risk receives careful analysis, particularly by counterparties entering into caps and swaps agreements. This
section of t h e article takes a detailed look at
how default risk is evaluated a n d how it affects
the pricing of caps, collars, a n d floors.
The first aspect of t h e p r o b l e m is t o consider
the precise nature of t h e default risk or, alternatively, t h e credit exposure. If a cap is in t h e
money on a floating-rate reset date, t h e owner of
the cap expects to receive a payment from t h e
cap writer, as reviewed above. If t h e writer is
insolvent and thus fails to m a k e the payment,
the owner is again in an u n h e d g e d position a n d
must m a k e t h e full floating-rate payment, b u t
this is not t h e only c o n s e q u e n c e of default. Provided t h e default d o e s not occur on t h e final
reset date, t h e c a p was also hedging future reset
dates, which u p o n default are also fully exposed. Thus, credit exposure d e p e n d s on the
t i m e that default occurs in the life of a cap agreement. (Note that a parallel argument can b e
m a d e for floors and collars.) The cost of default
to t h e cap buyer is the cost of replacing the
original cap with a new cap from another seller. If
interest rates at the default d a t e were identical
to t h e initial interest rates and t h e volatility had
not changed since t h e original cap was purchased, the replacement cost of t h e cap would
b e zero, ignoring transactions costs and differences in credit risks. That is, t h e cost of a new
cap for the remaining reset dates would exactly
equal t h e current market value of the existing
cap (if default had not occurred).
The next a n d rather complex aspect of t h e
credit risk question to consider concerns the
m e t h o d of assessing credit risk when a cap is
sold. Bankruptcy of a cap writer has n o impact
on cap buyers as long as the c a p stays out of t h e
money a n d the cap buyer has n o intention of
selling the cap before its term ends. Default
16
occurs only when a c a p is in the money a n d the
cap writer is bankrupt. The likelihood of bankruptcy may also b e related to the level of interest rates and thus d e p e n d e n t on the future
path of these rate movements. In addition, as
just discussed, a cap's replacement cost is a
function of where in the life of the cap agreem e n t default occurs. All of these factors should
b e weighed in evaluating what t h e potential
cost of default could b e and how that should
affect t h e price of a cap.
Marcelle Arak, Laurie S. G o o d m a n , and Arthur
Rones (1986) propose a m e t h o d of computing
credit exposure for caps, collars, a n d floors.
Their approach amounts to considering different worst-case scenarios that are defined by
t h e d e g r e e t o which a c a p can m o v e in t h e
money. For a cap t h e c o m p u t e d exposure de-
"T/ie cost of default to the cap buyer is
the cost of replacing the original cap
with a new cap from another seller."
p e n d s on t h e size of t h e upward m o v e m e n t in
t h e interest rate that could occur during each
reset interval. A cap's replacement value will
tend at first to increase early in the life of t h e
instrument a n d then to decrease toward the
e n d of the contract. The credit exposure is taken
t o b e t h e maximum replacement value comp u t e d at the reset dates. For example, if the
interest-rate volatility based on three-month
LIBOR is 10 percent (as measured by t h e annual
standard deviation), over a three-month period
t h e volatility is 0.10 Xv/( 1/4) = 5 percent. 3 4 Assuming an initial 7 percent LIBOR, three m o n t h s
later t h e u p w a r d m o v e w o u l d b e t o 7.35
|7.0 + (0.05 x 7.0)|. Given this rate and a further
assumption that rates at all other maturities
shifted in parallel, t h e cap replacement value is
calculated. Another 5 percent upward move is
then c o m p u t e d , giving a new LIBOR of 7.72
17.35 + (7.35 x 0.05)1 and again the replacement
ECONOMIC REVIEW, NOVEMBER/DECEMBER 1989
value is c o m p u t e d , and so forth. The credit
exposure is the maximum value of the replacement cost during the cap agreement.
A more conservative evaluation of credit exposure might assume that rates rose by two
standard deviations per year instead of one as
in the previous example. At two-standarddeviation moves, the actual exposure would, on
average, exceed the maximum computed amount
only 2.5 percent of the time (as compared to
exceeding it 16.5 percent of the time using a
one-standard-deviation measure). 35 Arak, Goodman, and Rones give an example of the credit
exposure on various collar agreements with a
floor equal to 6 percent and a cap equal to 9 percent. For three-month reset intervals, the exposure is 0.44 percent of the notional principal
(two-year collar), 0.82 percent (five-year collar),
"Computations based on worst-case
scenarios implicitly overstate the actual incidence of default because of
the arbitrary assumption about sequential interest-rate moves only in
one direction. "
and 2.68 percent (10-year collar). 3 6 By these
researchers' calculations, the credit exposure
on collars is rather small, especially compared
to similar calculations for other instruments
they consider, such as interest-rate swaps and
forward contracts. These calculations are intended for commercial banks, which set credit limits
for particular customers in order to manage the
size of potential losses in the event of default.
However, the method put forth by Arak, Goodman, and Rones is not useful for pricing caps—
that is, for adjusting the price or rate for the
anticipated cost of default. Computations based
on worst-case scenarios implicitly overstate the
actual incidence of default because of the arbitrary assumption about sequential interest-rate
moves only in one direction. A more desirable
approach would c o m p u t e the "expected value"
of default—the difference between caps not
subject to default and those that are.
FEDERAL RESERVE BANK OF ATLANTA
Caps as Default-Risky Options. Almost all of
the option pricing models used to value caps
ignore default risk. An exception is the model
proposed by Herb Johnson and Stulz (1987), in
which they derive formulas for default-risky or
"vulnerable" puts and calls. Unfortunately, their
formulas cannot b e straightforwardly applied to
caps, collars, or floors because of the t i m e
dimension involved in these options-based instruments. As has b e e n emphasized, caps are a
s e q u e n c e of options—default-risky options.
Fulfilling a given option contained in a cap
depends on the absence of bankruptcy at earlier
reset dates. If bankruptcy occurred earlier, the
current option would not b e honored by the cap
writer. The sequential time dimension involved
in valuing caps makes the mathematics formidably complex. 3 7
This author has tackled the complexity of cap
valuation by using computer-intensive methods
to handle the intricate contingencies implied in
cap, collar, floor, and swap agreements (Peter A.
Abken |forthcoming|). His c o m p u t e r m o d e l
avoids the contradictory assumption inherent in
the Black model used for short-term d e b t options—that short-term interest rates are constant—but at the cost of trading off a simple
analytical formula for a complicated computer
algorithm. Nevertheless, the intuition behind
the new model is simple and easily explained.
The value of a European option can be thought
of as the average or expected value of its payoffs
at expiration, discounted back to the present.
Options are difficult to value because the payoff
upon expiration is a "kinked," or discontinuous,
function of the underlying asset price. A call
option is worth zero if the underlying asset price
at expiration is less than the strike price, and
positive in value if the underlying asset price
exceeds the strike price, increasing dollar for
dollar with the amount above the strike. The
Black-Scholes and Black formulas c o m p u t e the
value of a call as the expected value of the future
payoffs. 38 S o m e payoffs are more likely to occur
than others, and the formulas account for the
probabilities associated with the payoffs.
M o n t e Carlo S i m u l a t i o n . O n e m e t h o d for
valuing options relies on extensive computations to determine the expected payoffs.
Known as Monte Carlo simulation, this process
was first applied to option pricing problems by
Phelim P. Boyle (1977). The standard application
II
involves stock option pricing. A stock price, on
which an option is valued, is assumed to rise
and fall randomly overtime, although its value at
any point can b e described in terms of its statistical distribution, which is known or assumed. In
standard problems the distribution for stock
price changes is assumed to b e fully characterized by its mean and variance. Using this
information, artificial future stock-price paths,
also known as realizations,
can b e created
numerically by computer. By randomly generating a large enough number of price paths (tens
of thousands, at a minimum) and evaluating the
payoff on an option with a given strike price at a
particular point in time—the option's expiration
date—an average over these randomly generated payoffs can b e made. The option price is
given by appropriately discounting the expected future payoff into current dollars. Of course,
the Black-Scholes formula accomplishes t h e
same thing mathematically and is conceptually
equivalent. To the penny, both methods will
give the same price using identical assumptions regarding the statistical characteristics of
stock price movements. The Monte Carlo method, though cumbersome, pays off in cases where
the asset price moves in unusual ways, such as in
random jumps—for example, d u e to a stock
market crash. The Black-Scholes model rules
out such movements by assumption. Cap valuation is another area where Monte Carlo methods
offer a simplification over approaches that may
not otherwise b e mathematically tractable.
Three factors taken together contribute to the
complexity of default-risky cap valuation. The
first is that d e b t prices on instruments like
Treasury bills or Eurodollar deposits vary with
interest rates. Second, each constituent option
in a cap is subject to default and must b e valued
as a default-risky option. Third, the payoff on a
given option d e p e n d s on the nonoccurrence of
default on options from earlier periods.
The payoff of a vulnerable call option is the
lesser of the firm's value or the default-free
option payoff. The value of the firm is the market
value of its equity (before including the value of
its cap). If the value of the firm that sold the
option is greater than the payoff, no default
occurs. If the payoff exceeds the firm's value, the
company defaults and the option holder receives the value of the firm—or some share of it,
as determined by the bankruptcy courts—when
18
the company is liquidated. In view of the fact
that a vulnerable call may pay off less, b u t never
more, than a default-free call, the value of a
vulnerable call must b e less than the value of an
otherwise comparable default-free call.
An additional consideration for cap valuation,
as discussed above, is that default on a cap
leaves the cap buyer unhedged. The exposure
is t h e replacement value of the cap. Thus,
default involves at a minimum replacement of
the missed option payoff, and possibly t h e
entire remaining value of the cap, if the firm
wants to maintain the hedge. Thus, besides
valuing default-risky call options, cap valuation
must also evaluate such replacement costs.
The Elements of the Caps Model. To convey
the basic ideas behind construction of the caps
model, this section of the article sketches out
"An additional consideration for cap
valuation ...is that default on a cap
leaves the cap buyer unhedged. The
exposure is the replacement value of
the cap."
the model, the technical details of which can b e
found in Abken (forthcoming). Three so-called
state variables are computer-generated to implement the simulation. The options making u p
a cap are valued based on the underlying interest rate, as discussed earlier. The entire path
of the term structure of interest rates is generated using the model developed by Stephen
M. Schaefer and Eduardo S. Schwartz (1984). Two
state variables are the difference or spread between the instantaneous rate and a consol rate
(that is, t h e rate on a b o n d having infinite
maturity), and the consol rate itself. All other
intermediate-maturity d i s c o u n t b o n d s are
derived by formula from these two inputs, which
describe absolute and relative movements in
interest rates at all maturities. The third state
variable represents the value of the firm, which
also fluctuates randomly over time, reflecting
unpredictable changes in interest rates, earnECONOMIC REVIEW, NOVEMBER/DECEMBER 1989
ings, and other variables that determine firm
value.
The example to b e considered is parallel to
the one discussed earlier in Table 1, but the
focus is now on credit risk. The cap model will
value two-year caps on a three-month interest
rate. The cap consists of seven reset dates, at
each of which the firm's value is compared to the
call option payoff. Default-free and default-risky
caps are valued. The difference in the price or
rate for these otherwise identical caps is the
credit spread for default risk. The example developed below illustrates how default risk is
particularly sensitive to t h e correlation over
t i m e b e t w e e n firm value a n d interest-rate
movements.
The parameter values for t h e SchaeferSchwartz m o d e l were estimated from actual
"[Djefault risk is particularly sensitive
to the correlation over time between
firm value and interest-rate movements. "
interest-rate data on one-month Treasury bill
and 30-year b o n d yields, which served as proxies for the instantaneous interest rate and consol interest rate, respectively. The rates were
sampled weekly on Fridays from January 1983 to
August 1989. The reader is referred to Abken
(forthcoming) for details concerning parameter
estimation and other technical details concerning the model.
A simplification used in the simulations presented in this article is that whenever a default
occurs—that is, when the firm value is less than
the option payoff—the replacement value of the
cap is not computed. Instead, the option payoff
for that reset date is set equal to the negative of
the payoff. In other words, the cap owner has to
cover the full floating-rate interest payment for
that date. Payoffs at future reset dates are assumed to b e zero. Valuing a new cap at current
rates would increase the cost of default com-
pared to the procedure used here; such valuation, however, would also require separate
simulations at each occurrence of default.
M o r e Examples. Table 2 gives the results of
the simulations. Three panels of this table differ
only in the degree that firm value is correlated
with interest-rate movements. In the SchaeferSchwartz model, there are two elements to this
correlation. Firm value can b e correlated with
consol rate movements or spread movements,
or both. (TheSchaefer-Schwartz model assumes
that the spread and consol rate are uncorrelated, which is supported by empirical research.)
Correlation coefficients range from — 1, perfect
negative correlation, to 1, perfect positive correlation. Intuitively, a cap writer whose firm
value is negatively correlated with interest-rate
movements poses a greater credit risk than o n e
that is positively correlated. For a given strike
level, when interest rates are high, caps are
more likely to b e in the money and require a
payment from the writer. A negative correlation
therefore means that high interest rates are
associated with low firm value; hence, default is
more probable than it would b e for zero or positive correlations. Also, empirically short- and
long-term interest rates are positively correlated. Thus, a negative correlation of firm
value and long-term interest rate would also b e
associated with a negative correlation between
the firm value and interest-rate spread (defined
as the short rate less the long rate).
Panel A gives the base case of zero correlation
of firm value with the interest-rate spread and
with the long-term interest rate. The annual
default rate for this case is set to 0.13 percent by
adjusting the initial value of the firm to give this
rate as the outcome of the simulations. 39 The
same initial firm value is then used in panels B
and C, thereby yield ing new default rates d u e to
different correlations with the term structure
variables. The initial term structure has a spread
of 2.7 percentage points, which was the average
spread over the sample period. The short-term
interest rate is initially 8 percent and the cap is
written at 9 percent. As in Table 1, the option
rates are given for each reset date. This table
includes default-free and default-risky options;
the sum over reset dates for each type is the cap
rate. Because the default rate is so low, the discrepancies between default-free and defaultrisky option prices d o not become significant
II
FEDERAL RESERVE BANK OF ATLANTA
Table 2.
Default-Free and Default-Risky Cap Rates
Estimated by Monte Carlo Simulation, 9.0 Percent Two-Year Cap
Initial term structure: Short-term rate, 8.0 percent; Long-term rate, 10.7 percent
Panel A: Correlation of firm value with interest-rate spread: 0
Correlation of firm value with long-term rate: 0
1
13
7.94
7.94
Reset date number:
Time to expiration (weeks):
Default-free option rate:
Default-risky option rate:
Default-free cap rate:
Standard deviation:
95 percent confidence interval:
2
26
17.99
17.99
3
39
26.95
26.95
4
52
35.57
35.53
5
65
43.98
43.81
Default-risky cap rate:
Standard deviation:
95 percent confidence interval:
244.16
(1.45)
(241.32, 247.00)
Credit spread in basis points:
Standard deviation:
95 percent confidence interval:
Annual default rate:
6
78
51.87
51.34
7
91
59.86
58.71
242.28
(1.43)
(239.48, 245.08)
1.89
(0.14)
(1.62, 2.16)
0.13 percent
Panel B: Correlation of firm value with interest-rate spread: -0.5
Correlation of firm value with long-term rate: -0.5
1
7.94
7.94
Reset date number:
Default-free option rate:
Default-risky option rate:
Default-free cap rate:
Standard deviation:
95 percent confidence interval:
2
17.99
17.98
3
26.95
26.79
4
35.57
34.98
5
43.98
42.19
Default-risky cap rate:
Standard deviation:
95 percent confidence interval:
244.16
(1.45)
(241.32, 247.00)
Credit spread in basis points:
Standard deviation:
95 percent confidence interval:
Annual default rate:
6
51.87
48.15
7
59.86
53.51
231.54
(1.35)
(228.89, 234.19)
12.63
(0.35)
(11.94,13.32)
0.71 percent
Panel C: Correlation of firm value with interest-rate spread: 0.5
Correlation of firm value with long-term rate: 0.5
1
7.94
7.94
Reset date number:
Default-free option rate:
Default-risky option rate:
Default-free cap rate:
Standard deviation:
95 percent confidence interval:
2
17.99
17.99
3
26.95
26.95
Sample
20
size for each panel:
50,000
independent
5
43.98
43.98
Default-risky cap rate:
Standard deviation:
95 percent confidence interval:
244.16
(1-45)
(241.32, 247.00)
Credit spread in basis points:
Standard deviation:
95 percent confidence interval:
Annual default rate:
Note:
4
35.57
35.57
draws.
6
51.87
51.87
7
59.86
59.86
244.16
(1.45)
(241.32, 247.00)
0.0
(0.0)
(0.0,0.0)
0.0 percent
Cap rates expressed
in basis
points.
ECONOMIC REVIEW, NOVEMBER/DECEMBER 1989
until t h e later reset dates. The default-free cap
rate is 244.16 basis points, whereas t h e defaultrisky cap rate is 242.28. The difference of 1.89
basis points is the credit spread.
These figures are estimates and have an error
associated with them. O n e can arbitrarily red u c e that error by increasing the n u m b e r of
realizations u s e d t o c o m p u t e t h e o p t i o n s .
Q u a d r u p l i n g t h e n u m b e r of realizations reduces the standard deviation by half. The simulations for each p a n e l were g e n e r a t e d by
taking 50,000 i n d e p e n d e n t sets of realizations
of t h e state variables. 40 The standard deviation
and 95 percentconfidence intervals for each cap
rate and the spread are reported in Table 2.
The simulation used t o generate panel B was
the s a m e as that for panel A in all respects
except that t h e correlation between firm value
and interest-rate spread is —0.5 instead of zero,
a n d t h e correlation b e t w e e n firm value a n d
long-term rate is —0.5 instead of zero. The results show a substantial increase in the incidence of default. The b a s e rate in panel A for
zero correlations is 0.13 percent, whereas the
negative correlations in panel B raise the default rate to 0.71 percent. The credit spread rises
from 1.89 basis points to 12.63 basis points. As
discussed previously, the reason is that firm
value is likely to b e low when interest rates are
high. The cap writer has a greater chance of
being insolvent when a payment is required. As
a final example, the correlations in panel C take
the o p p o s i t e signs from those in panel B. The
credit spread and annual default rate drop to
zero. The greater chance of high firm value coinciding with cap payments reduces the likelihood of default by t h e c a p writer; in this case,
the incidence of default drops to zero.
The substantial increase in t h e credit spread
exhibited in panel B may exaggerate default risk
for two reasons. First, t h e cap is assumed t o b e
u n h e d g e d by the firm. In other words, t h e company is taking a speculative position. Actual cap
writers usually take offsetting positions in other
caps or h e d g e by other methods, at least to
s o m e degree. Second, the model assumes that
failure to cover cap payments is t h e only factor
causing bankruptcy. For actual cap writers, the
contingent liability posed by a cap is probably
small compared to other items on the balance
sheet. O n the other hand, the c o m p u t e d credit
spread may still b e a good approximation if the
c a p serves as a proxy for t h e firm's overall
balance sheet exposure to movements in interest rates.
No data on actual credit spreads are published. In conversations with the author, cap
market participants place t h e credit spreads
that have occurred in the range of 5 to 10 basis
points for two- to three-year caps. The estim a t e d spreads using t h e cap model are roughly in that range. Further research into actual
credit s p r e a d s a n d r e f i n e m e n t s of t h e c a p
m o d e l should sharpen t h e estimation results
a n d m a k e the m o d e l more useful.
Conclusion
Interest-rate caps, collars, a n d floors are
a m o n g the newest interest-rate risk managem e n t instruments. This article has given an
exposition of these closely related instruments,
which are options-based and designed to limit
exposure t o fluctuations in short-term interest
rates on floating-rate assets or debt. Their applications are not limited to hedging. Like options, they are also convenient for speculating
on interest-rate movements. In practice, however, the distinction between these two applications is rarely clear-cut. Several e x a m p l e s
served to illustrate how financial managers use
caps, collars, a n d floors.
The article also discussed the credit risks
associated with caps, collars, and floors, which
for the most part are over-the-counter contracts
offered by o n e firm to another. Default risk is
inherent in this kind of arrangement and can b e
priced. A new cap valuation model produced
credit spreads that are not much different from
those observed in the cap market between
stronger a n d weaker credit risks a m o n g c a p
writers. Interest-rate risk m a n a g e m e n t has b e e n
growing in importance for financial managers.
This article may improve their understanding of
the credit risk of caps, collars, and floors and
h e l p d e t e r m i n e the cost of interest-rate protection.
II
FEDERAL RESERVE BANK OF ATLANTA
Notes
' R e c e n t Economic
Review
Koch (1988), a n d Feinstein (1989).
2
Uses Incentives t o Push Rate Collars," American
articles i n c l u d e A b k e n (1987),
Feinstein a n d G o e t z m a n n (1988), Kawaller, Koch, a n d
' 8 T h e s e e x a m p l e s are consistent with the recent findings of
Boyle a n d Turnbull (1989) in their examination of collars.
S e e Wall a n d Pringle (1988) for an introduction t o interest-
Using a different option-pricing m o d e l t h a n t h e Black
rate swaps.
3
m o d e l , they f o u n d that a 100 percent increase in t h e
For brevity, the market for caps, collars, a n d floors will b e
referred t o as t h e c a p
4
volatility causes t h e floor level t o c h a n g e by less than o n e
market
basis p o i n t . If their f i n d i n g s are also valid for the Black
S e e Kuprianov (1986): 16-20, for a discussion of Eurodollar
m o d e l , m o s t of t h e difference observed in the e x a m p l e s
d e p o s i t s a n d Eurodollar futures.
5
in t h e text is a t t r i b u t a b l e t o t h e d i f f e r e n c e in yield
T h e i n f o r m a t i o n o n t h e 1SDA survey was r e p o r t e d in
Risk 2 (April 1989): 11.
6
A d e t a i l e d discussion of o p t i o n pricing is b e y o n d t h e
curves.
19
Before March 1989, contract expiration d a t e s h a d a maxim u m maturity of o n e year. S e e Chicago Mercantile Ex-
s c o p e of this article. A basic overview can b e f o u n d in
c h a n g e (February/March 1989): 7.
A b k e n (1987). S e e Cox a n d R u b i n s t e i n (1985) or larrowand
R u d d (1983) for m o r e thorough introductions t o o p t i o n
20
T h e term counterparty
S e e A b k e n (1987): 6, for m o r e detail,
2
' A n o t h e r c o m p l i c a t i o n in using futures in a replicating
portfolio is that futures contracts are marked to market
^ e e H e n d e r s o n (1986) for further discussion.
9
10
daily. This situation may create cash flow p r o b l e m s since
S e e Black (1976).
futures positions that lose value may b e subject to fre-
Tb the author's knowledge, n o p u b l i s h e d s t u d i e s have
q u e n t margin calls. Even t h o u g h the replicating portfolio
c o m p a r e d t h e accuracy of different option-pricing m o d e l s
is u s e d to h e d g e a cap, which matches it in value, the cash
for pricing caps a n d related instruments. O n e reason may
flows from t h e c a p c o m e only w h e n it is sold a n d o n
b e that there are n o publicly available d a t a o n t h e s e rates,
a n d a n o t h e r is that t h e s e instruments are relatively new.
interest p a y m e n t dates.
22
S e e A b k e n (1987) for m o r e on t h e synthetic creation of
Little empirical research exists o n t h e a d e q u a c y of dif-
options. Mattu (1986) gives e x a m p l e s of replicating port-
ferent interest-rate o p t i o n - p r i c i n g m o d e l s . Boyle a n d
Turnbull (1989) u s e t h e C o u r t a d o n option-pricing m o d e l
folios for c a p s a n d floors.
23
in evaluating collar rates, b u t they d o n o t c o m p a r e their
Shirreff (1986) gives an i n t e r e s t i n g t h o u g h
in it.
ket rates.
' B e c a u s e t h e C M E a n d m o s t LIFFE Eurodollar futures are
"cash-settled," a $1 million d e p o s i t is rarely m a d e , b u t
instead only t h e difference b e t w e e n t h e current, or spot,
24
L e G r a n d a n d Fertakis (1986): 134.
25
Floating-rate C D s are also called variable-rate CDs.
26
S e e Intermarket
(October 1986): 14, for an account of t h e
first such sale of a c a p from a c a p p e d floating-rate n o t e
LIBOR a n d the contracted LIBOR t i m e s t h e notional prinl2
somewhat
d a t e d overview of t h e c a p s market a n d t h e various players
rates with t h o s e from other m o d e l s nor with actual mar1
is standard terminology for t h e
other party in a swap, c a p , floor, or collar agreement.
pricing.
7
Banker,
August 2, 1989.
cipal actually changes hands.
(FRN). By selling a c a p off an issue of $100 million in 12-
Prior to )une 1989 contract m o n t h s extended three years.
year c a p p e d FRNs, B a n q u e I n d o s u e z of Paris lowered its
I3
interest rate by o n e - e i g h t h of a p o i n t b e l o w LIBOR.
A Eurodollar futures price is actually a n index value that
e q u a l s 100 m i n u s the "add-on" yield (three-month LIBOR).
U n c a p p e d , t h e n o t e s w o u l d h a v e s o l d at LIBOR. T h e
Thus, t h e futures price a n d add-on yield m o v e inversely
c a p p e d FRNs were issued at LIBOR p l u s three-eighths.
with each other. S e e Kuprianov (1986): 16, for m o r e d e t a i l
O n an a n n u a l basis, I n d o s u e z therefore collected the
o n Eurodollar futures a n d short-term interest-rate futures
generally. Both the add-on yield a n d t h e futures price are
usually q u o t e d in t h e financial press.
l4
e q u i v a l e n t of 50 basis p o i n t s o n t h e sale of its cap.
27
Shirreff (1986): 29.
28
T h e volatilities shown i n C h a r t I are p r o b a b l y not t h e s a m e
S e e Feinstein (1989) for d e t a i l s o n t h e estimation, inter-
as t h o s e u s e d to generate t h e c a p rates. The volatilities
pretation, a n d uses of i m p l i e d volatilities. T h e Eurodollar
were o b t a i n e d from a different source t h a n t h e c a p rates,
futures o p t i o n s are actually American options, b u t t h e
b u t t h e y s h o u l d b e highly c o r r e l a t e d with t h e actual
early exercise feature has negligible value for t h e slightly
volatilities u s e d to price t h e caps.
out-of-the-money o p t i o n s usually u s e d in estimating the
29
N e w b e r y a n d Stiglitz (1981) give a c o m p r e h e n s i v e discus-
30
Wall a n d Pringle (1988): 22.
sion of risk aversion a n d t h e rationale for hedging.
i m p l i e d volatilities with a E u r o p e a n futures o p t i o n formula.
l5
S u m s in Table 1 m a y n o t a d d u p d u e t o r o u n d i n g error. C a p
rates a r e usually r o u n d e d t o w h o l e b a s i s p o i n t s . T h e
16
3
' T h e e x a m p l e given was d e s c r i b e d in terms of a "flow conc e p t " of interest-rate risk, that is, t h e i m p a c t of a c h a n g e in
dollar a m o u n t s are t h e exact a m o u n t s c o m p u t e d in con-
interest rates o n the net interest margin. Another way to
structing Table 1.
view interest-rate risk is in t e r m s of a "stock c o n c e p t , " t h e
A n o t h e r way to create a zero-cost collar is t o set the floor
change in the net worth of t h e firm. A parallel shift in t h e
first a n d then d e t e r m i n e t h e a p p r o p r i a t e cap. T h e m e t h o d
term structure of interest rates w o u l d r e d u c e t h e value of
discussed in t h e text is m o r e c o m m o n .
an S&L's long-term mortgages m o r e than it would r e d u c e
' 7 Collars have also b e e n offered that give t h e buyer a pay-
t h e value of its short-term liabilities. Net worth w o u l d b e
m e n t for taking t h e collar, that is, the value of t h e floor sold
r e d u c e d or possibly turn negative. Purchasing a c a p - a n
exceeds t h e cost of t h e c a p purchased. S e e "NatWest
asset o n the b a l a n c e s h e e t - w o u l d offset loss of net worth
22
ECONOMIC REVIEW, NOVEMBER/DECEMBER 1989
t o s o m e extent b e c a u s e it would gain value as interest
plexities involved in valuing securities that are c o m p o s e d
rates rise. S e e Spahr, Luytjes, a n d Edwards (1988) for a
g o o d exposition of this a p p l i c a t i o n of c a p s a n d how they
of s e q u e n c e s of options.
38
h e d g e interest-rate risk.
32
average of all p o s s i b l e payoffs, each payoff m u l t i p l i e d by
the probability of its occurring.
C o m m e r c i a l b a n k s u n d e r w r i t i n g d e b t for highly levera g e d financings often require their floating-rate borrow-
39
According to Moody's study, t h e lowest investment-grade
ers to buy caps for a portion of t h e d e b t . This h e d g i n g
b o n d s , rated Baa (or BBB by Standard a n d Poor's), h a d
r e q u i r e m e n t may b e s t i p u l a t e d in t h e loan covenant. S e e
average a n n u a l d e f a u l t rates over two-year h o r i z o n s of
Richardson (1989): 12.
0.25 percent. A Standard a n d Poor's BBB-rated investment
b a n k was reportedly at a disadvantage in writing caps
33
S e e Moody's
34
This m e t h o d a s s u m e s that t h e interest rate follows a ran-
Special
(1989).
Report
c o m p a r e d t o stronger writers. S e e Shirreff (1986): 34.
d o m walk with n o " d r i f t " (that is, d e t e r m i n i s t i c t r e n d
The 0.13 default rate used in the e x a m p l e was chosen t o
movements). C h a n g e s in t h e interest rate from p e r i o d to
reflect t h e lower risk of default o n a c a p relative t o a
period are a s s u m e d t o b e normally d i s t r i b u t e d with constant variance (or standard deviation), implying that the
statistical distribution of interest-rate m o v e m e n t s may b e
35
l n a discrete t i m e m o d e l the expected value is a weighted
bond.
40
T h e M o n t e Carlo s i m u l a t i o n s u s e d a variance reduction
t e c h n i q u e called t h e m e t h o d of antithetic variates (see
c o m p l e t e l y characterized by only its m e a n a n d variance.
Boyle 11977|). The total n u m b e r of realizations was in fact
These percentages are b a s e d o n t h e properties of t h e nor-
200,000 for each simulation, though only a fourth of that
mal distribution, which is a s s u m e d to describe interest-
n u m b e r c a m e from i n d e p e n d e n t draws from t h e r a n d o m
rate m o v e m e n t s .
n u m b e r generator. S e e A b k e n (forthcoming) for m o r e
36
Arak, G o o d m a n , a n d Rones (1986): 452.
details.
37
C a p valuation can b e formulated as a kind of c o m p o u n d
o p t i o n p r o b l e m . S e e G e s k e (1977) t o a p p r e c i a t e t h e com-
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Arak, Marcelle, Laurie S. G o o d m a n , a n d Arthur Rones.
"Credit Lines for New Instruments: Swaps, Over-theCounter O p t i o n s , Forwards a n d
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Kawaller, Ira G „ Paul D. Koch, a n d Timothy W. Koch. "The
Boyle, Phelim P., a n d Stuart M. Turnbull. " P r i c i n g a n d Hedg9 (Feb-
ruary 1989): 41-54.
Relationship b e t w e e n t h e S&P 500 Index a n d S&P 500
Index Futures Prices." Federal Reserve Bank of Atlanta
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Management
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(Winter 1988): 45-58.
" C a p s a n d Floors." The Banker
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LeGrand, Jean E„ a n d John P. Fertakis. "Interest Rate C a p s :
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Spahr, Ronald W„ )an E. Luytjes, a n d D o n a l d G. Edwards.
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Wall, Larry D. "Alternative Explanations of Interest Rate
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Shirreff, David. " C a p s a n d O p t i o n s : T h e D a n g e r o u s New Protection Racket." Euromoney
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Sutherland, L. Frederick. " S q u e e z i n g Cash: How t o Make an
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Schaefer, S t e p h e n M„ a n d E d u a r d o S. Schwartz. "A TwoSolution." lournal
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Quan-
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Wall, Larry D„ a n d )ohn ). Pringle. "Interest Rate Swaps: A
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37.
24
ECONOMIC REVIEW, NOVEMBER/DECEMBER 1989
Federal Reserve Bank of Atlanta
1989 Annual Report
The Atlanta Fed's 1989 Annual Report will be available in February 1990. In
addition to reviewing the Bank's activities during 1989, the report will include
selections from its 75th anniversary publication, A History of the Federal Reserve
Bank of Atlanta, 1914-1989. It will also contain a statement of condition, a statement of earnings and expenses, and a statistical summary of operations, along with
a list of directors and officers who served during the year.
For copies of the publication, please fill out the coupon below and mail to:
Public Information Department, Federal Reserve Bank of Atlanta, 104 Marietta
Street, N.W., Atlanta, Georgia 30303-2713, or call 404/521-8788.
Please s e n d m e
c o p y (copies) of t h e Atlanta Fed's 1989
Annual Report.
Name
Address
City
State
ZIP.
Financial Asset Pricing Theory:
A Review of Recent Developments
Ellis W. T a l l m a n
In this article, an Atlanta
Fed economist reviews research on financial asset pricing with a special focus on
the links between asset pricing and the real economy. Surveying
the capital asset pricing model (CAPM),
the consumption-based CAPM, and the more recent arbitrage pricing theory, he concludes that ongoing
theoretical and empirical developments point toward future research that can link real economic factors to
asset pricing behavior.
Financial asset pricing theories have devel-
firm's stock. C o m p e t i t i v e market forces t h e n b i d
o p e d primarily over t h e p a s t 30 years. Scholars
t h e asset price u p or d o w n to its n e w equilib-
have m a d e great strides d u r i n g t h e latter half of
rium price.
t h e p e r i o d in t h e analysis of newer, m o r e dy-
This framework provides an intuitive link be-
n a m i c m o d e l s . This article surveys recent de-
t w e e n t h e asset markets a n d m e a s u r e s of real
v e l o p m e n t s in t h e o r e t i c a l research a n d t h e
e c o n o m i c behavior. Such a m o d e l suggests that
state of relevant empirical evidence. It con-
t h e aggregate stock m a r k e t v a l u e reflects expec-
c l u d e s that financial asset pricing research re-
tations of t h e p r e s e n t d i s c o u n t e d v a l u e of cash
m a i n s o p e n for a d d i t i o n a l study, yet t h e current
flows from t h e future performance of t h e econ-
b o d y of k n o w l e d g e presents a coherent frame-
omy. D e s p i t e t h e intuitive a p p e a l of a correla-
work for analyzing asset pricing in a rational
tion b e t w e e n p e r f o r m a n c e of t h e stock market
e c o n o m i c setting.
a n d t h e real e c o n o m y , insufficient e m p i r i c a l
M o d e r n c a p i t a l m a r k e t theory s t u d i e s t h e
e v i d e n c e exists to s u p p o r t this relationship.
d e t e r m i n a t i o n of asset prices. In a basic m o d e l
For e x a m p l e , from O c t o b e r 2 to O c t o b e r 23,
of stock valuation, asset prices reflect t h e pres-
1987, nearly 30 percent of perceived asset v a l u e
e n t d i s c o u n t e d v a l u e of t h e projected future
in t h e stock market, as m e a s u r e d by t h e Stan-
d i v i d e n d p a y m e n t s to t h e stockholder. W h e n
d a r d a n d Poor's 500, was lost. In contrast, t h e
n e w information a b o u t a firm's prospects be-
real e c o n o m y g r e w a n d c o n t i n u e d t o grow
c o m e s public, expectations a b o u t future cash
t h r o u g h o u t 1987 a n d 1988 a n d into 1989. In long-
flows or t h e risk-adjusted d i s c o u n t rate of a
er perspective, o n t h e other h a n d , t h e overall
given stock change. In m o s t m o d e l s of asset
growth rate of real gross national p r o d u c t (GNP)
pricing, investors, lenders, a n d other e c o n o m i c
averaged 4.2 p e r c e n t from 1983 through 1988,
" a g e n t s " are a s s u m e d to b e rational, using n e w
a n d t h e stock market b o o m has c o i n c i d e d , al-
information to a d j u s t their valuation of t h e given
t h o u g h not without volatility. The s o m e t i m e s
a n o m a l o u s behavior of t h e stock market vis-avis real G N P growth indicates that t h e forces t h a t
drive asset prices are still largely a mystery,
especially with regard to t h e relationship be-
The author
Atlanta
is an economist
Fed's Research
Department.
and Frank King for valuable
26
in the macropolicy
section
He thanks Curt
comments.
of the
Hunter
t w e e n real e c o n o m i c p e r f o r m a n c e a n d asset
markets.
ECONOMIC REVIEW, NOVEMBER/DECEMBER 1989
To respond to a n e e d for an u p d a t e on t h e
existing research on asset pricing, this article
offers a general introduction to and historical
survey of m o d e r n financial asset pricing theories; other surveys of asset pricing m o d e l s have
focused only on a specific subset of them. This
p a p e r concentrates on the recent developments in asset pricing m o d e l s under uncertainty in t h e 17 years since an early survey of the
groundbreaking research by Michael C. Jensen
(1972). Its primary purpose is to show that such
theories have p r o v i d e d useful advances in
achieving a better u n d e r s t a n d i n g of e q u i t y
market pricing. 1
Presented first is a brief summary of t h e traditional capital asset pricing m o d e l (CAPM) a n d
the groundbreaking work that d e v e l o p e d from
it. The survey then traces t h e evolution of t h e
initial work on the CAPM to asset pricing in
d y n a m i c m o d e l s , s o m e of which e n c o m p a s s
both the disciplines of finance and macroeconomics. While not exhaustive, t h e article conc l u d e s with suggestions for further work on
asset pricing that may b e especially useful to
those involved in economic policy-making or in
the application of asset valuation research.
Policymakers have a particular interest in better understanding linkages between real economic performance and asset pricing behavior.
Financial data such as stock market prices are
FEDERAL RESERVE BANK OF ATLANTA
observed much more often than are most real
economic data like industrial production and
gross national product, which are available only
monthly or quarterly. Such financial statistics
may provide preliminary insights into the condition of real economic prospects, thus enhancing
t h e policymaker's information set. Also, specific
information on risk sources in the real economy
can help policymakers promote a stable environment for financial markets and foster more
efficient allocation of capital in the economy.
Investment managers may also find the isolation of macroeconomic sources of asset risk a
useful m e t h o d of assessing portfolio risk and a
criterion for portfolio formulation.
Valuation Theory, Mean Variance
Efficiency, and the Traditional CAPM
As long as stock markets have existed, prognosticators have tried to predict future movements in equity values. Forecasts often lacked a
strong theoretical a n d analytical framework,
though. Early attempts t o examine their effectiveness, notably by Alfred Cowles III (1933), suggested that they offered no perceptible advantages to investors. More formal and scientific
analysis of asset price behavior began later.
27
Harry Markowitz (1952) provided t h e source
for m o d e r n portfolio theory. His research is
often cited as the seminal work of m o d e r n finance from which evolved the early impetus t o
describe the equilibrium relationship between
assets a n d risk. The resulting asset pricing models, particularly t h e traditional capital asset
pricing m o d e l , rely on the return to a "market''
portfolio, consisting of a weighted average of all
assets held, as t h e benchmark from which o n e
can assess asset prices relative t o the market.
The CAPM provides a useful simplification a n d
focus for asset pricing theory because it produces an interpretable risk measure for a riskreturn relationship and parsimoniously summarizes a great deal of information in a single
variable.
A weakness of the early equilibrium asset
pricing m o d e l s , however, is their lack of any
formal linkage b e t w e e n real e c o n o m i c performance a n d t h e behavior of asset prices.
Recessions—or, m o r e generally, changes in future prospects for the economy—affect firm valuation by altering expected cash flows and t h e
relevant discount rate, b u t t h e s i m p l e CAPM offers no direct m e t h o d to incorporate fluctuations in economic conditions over t i m e into the
asset pricing process. The model ignores this issue. Recent theoretical advances in dynamic
m o d e l s of asset pricing as well as an accumulation of e v i d e n c e in conflict with t h e s i m p l e
CAPM have m a d e that basic formulation less
central as an equilibrium model of asset pricing. 2 Yet, the simple CAPM provides a major part
of the underlying intuition for these models.
Modern financial theory has its underpinnings in the application of scientific m e t h o d s t o
basic finance questions. Hundreds of different
assets trade on t h e stock exchange, and each
asset has characteristics, such as firm size, location, industry, and age, that distinguish it from
other assets. The simultaneous analysis of so
many characteristics is not feasible in a scientific realm. To focus attention on t h e most imp o r t a n t traits, financial m o d e l s simplify t h e
p r o b l e m by limiting t h e n u m b e r of variables.
O n e of the earliest m o d e l s of asset pricing,
briefly m e n t i o n e d above, analyzes the valuation
of a single stock as a function of t h e flow of future d i v i d e n d s discounted by the relevant riskrelated discount rate. The m o d e l , presented by
John B. Williams (1931), is outlined below:
28
where P, 0 is t h e price of asset / at period 0, di t is
the dividend per share of c o m m o n stock of firm /'
from the e n d of m o n t h t - 1 to the e n d of m o n t h
t, and kj is t h e risk-related rate of discount for
firm /'.
Eugene F. Fama and Merton H. Miller (1972)
s h o w that—given a n u m b e r of s i m p l i f y i n g
assumptions—firm valuations derived from disc o u n t e d firm cash flows, t h e stream of divid e n d s , or t h e firm's earnings p r o d u c e Williams's
result. Williams's m o d e l , in a d e t e r m i n i s t i c
world without uncertainty, thus offers a framework to g u i d e analysis. This valuation model,
altered for uncertainty, suggests that asset
prices vary u p o n the release of new information
regarding a firm's prospects.
Before t h e a n n o u n c e m e n t of t h e return on a
stock, a large degree of uncertainty exists regarding t h e actual outcome, that is, t h e return ex
post. 3 In modern financial theory, stock returns
are viewed as random variables, and a probability distribution is associated with them. For
most applications, stock return distribution has
b e e n assumed t o b e approximated by the normal distribution, which is fully s u m m a r i z e d by
two parameters: t h e mean, which is the measure of central tendency, a n d t h e variance, t h e
measure of dispersion around t h e central tendency. 4
Markowitz p r e s e n t e d a m o d e l of investor
portfolio selection under uncertainty in which
investors choose asset portfolios on t h e basis of
asset return a n d variance in a single period.
Portfolio optimization involves t h e trade-off between reward (expected return) a n d greater risk.
Investors prefer assets with higher m e a n s of
expected returns b u t lower return variances, or
less return variability. Thus, investors, assumed
to b e risk-averse, want to balance risk and return
in their portfolio choice.
A further insight of portfolio theory is that t h e
addition of a security a d d s to a portfolio's risk
mainly by t h e contribution of its variabil ity to the
variability of return from t h e entire portfolio—its
"covariance" with the return stream of other
portfolio assets. In the limit, as o n e increases
t h e n u m b e r of individual assets in a portfolio,
this covariance risk is t h e d o m i n a n t c o m p o n e n t
of financial asset portfolios' variance.
ECONOMIC REVIEW, NOVEMBER/DECEMBER 1989
This insight regarding covariation suggests
that a collection of assets can offer a lower level
of return variability than individual assets held
separately. Consider two assets whose returns
are perfectly negatively correlated. (The percentage increases in returns to o n e asset occur
simultaneously with equal b u t o p p o s i t e movements in another asset's return.) A portfolio of
these two assets would carry a fixed return a n d
no risk, or variability of return. Although such
neat covariation properties of assets d o not
often occur, t h e portfolio helps illustrate the
advantages of diversification.
A primary outgrowth from the Markowitz work
was the general equilibrium m o d e l s of asset
pricing credited most often to William F.Sharpe
(1964), John Lintner (1965), a n d Jan Mossin
(1966).5 These m o d e l s assume t h e existence of
an asset that is both free of default risk a n d
offers a fixed one-period return. 6 In equilibrium, all assets are held, a n d the market portfolio—as d e f i n e d earlier, t h e portfolio that
represents t h e return on every asset weighted
by its proportion in the total value of all assets
c o m b i n e d — c o m p r i s e s entirely risky assets.
James Tobin (1958) shows that in Markowitz's
environment, all individuals hold assets in only
two types of portfolios: the riskless asset and
the market portfolio.
The traditional capital asset pricing m o d e l ,
with fixed covariance between returns on an
asset and returns on the market portfol io, shows
that the risk premium of an asset (that is, the difference between the return on a risky asset and
the return on a risk-free asset) is determined by
movements in the market portfolio's expected
premium. For the purpose of this article, the
following equations present t h e main implications of the m o d e l :
and
C o v (/?,,
P /
~
o ^ )
RM)
'
where E, is t h e expected return to asset i, RF is
the rate of interest on the riskless asset, EM is
the expected return on t h e market portfolio, (3,is the degree to which asset i's return varies with
the market's return (discussed below), o 2 (RM) is
the variance of t h e return to market portfolio,
and Cov (/?, , RM) is t h e covariation between t h e
return to asset / and the return on the market.
FEDERAL RESERVE BANK OF ATLANTA
The main argument of the model relies on the
intuition that investors are rational a n d will
undertake risk only to t h e extent that they are
compensated. If, simply through diversification,
risk can b e removed from a portfolio, no o n e
should b e compensated for holding risk that
can b e avoided—"diversifiable" risk. While diversification can b e achieved by holding assets
that should have low or negative covariation,
Markowitz's portfolio theory result suggests that
holding a large n u m b e r of assets also results
in diversification.
Diversifiable risk should not b e related to a
risk premium. If a firm experiences a period of
poor m a n a g e m e n t or suffers a labor strike, the
asset returns may b e negative. But these sources
of risk are company- or firm-specific, and an
investor can reduce risk by investing a proportion of wealth in other firms. In contrast, certain
factors like wars or the oil price shocks of the
1970s affect t h e entire economy and, as a result,
future returns to the market portfolio. Such nondiversifiable
risk—that is, risk related t o covariation of an asset's return with the return to the
market portfolio—will therefore b e related to a
risk premium since an investor will require an
incentive to hold a risky group of assets.
For an individual asset /', the expected return
equals the riskless rate of interest plus the product of the market risk premium and the relevant
risk measure, (3,-, commonly referred to as the
risk of covariation with the market, or " b e t a " risk.
An implication of the model is that assets are
priced relative to their sensitivity to the market
portfolio returns. A portfolio in which 3 equals
o n e results in t h e s a m e expected return as t h e
market portfolio. Portfolios in which (3 is less
than o n e are referred to as defensive since they
should fluctuate relatively less than the market
b u t will also have a lower expected return. In
contrast, portfolios with (3 greater than o n e are
d e e m e d aggressive, in that their expected returns are greater than t h e market portfol io's, b u t
they incur relatively greater return volatility.
Thus, according to the CAPM only nondiversifiable, or systematic, risk is relevant for asset pricing: consequently, the expected return on any
asset is a linear function of the asset's (3. O n e
may interpret (3 as a sensitivity measure, gauging t h e reaction of the return on asset / to a
m o v e m e n t in the market return. Any returns that
are significantly greater or less than predicted
II
by an asset's beta-risk measure are called abnormal
returns.
Testing t h e C a p i t a l Asset P r i c i n g M o d e l .
Despite CAPM's simplicity and the measurability of its variables through market price data,
empirical evidence has not supported this approach. Two important empirical tests of the
CAPM—Fischer Black, Jensen, and Myron S.
Scholes (1972) and Fama and James D. MacBeth
(1973)—find evidence that conflicts with t h e
predictions of the simple Sharpe-Lintner pricing m o d e l introduced earlier. Black, Jensen, and
Scholes find evidence that low beta risk stocks
or portfolios have positive abnormal returns,
and high beta risk stocks or portfolios have
negative abnormal returns. 7
Fama and MacBeth included other measures
as additional explanatory factors in an asset
pricing regression to examine the CAPM's sensitivity to variables that theory suggests should
b e unimportant. The a d d e d measures—beta
s q u a r e d a n d t h e average of t h e residual
variance—might also indicate possible nonlinearities in t h e risk-return relationship. Although over the entire sample period their two
additional variables show no significant systematic relationship to priced risk, in certain
time periods these measures were associated
with statistically significant risk premia-that is,
the return which asset holders must b e paid in
order to induce them to accept an asset with
nondiversifiable risk. Fama and MacBeth concluded that these variables serve as proxies for
relevant underlying risk measures. 8 However,
their results suggest that a positive trade-off
generally exists between risk, as measured by
beta, and return.
In a recent paper that reexamines and extends the Fama and MacBeth estimates, Seha
M. Tinic and Richard R. West (1986) showed both
significant departures from t h e linear riskreturn trade-off predicted by the traditional
CAPM and significant nonlinearities not captured by the model. As a result, the researchers
conclude that results of existing empirical research on the traditional CAPM is suspect.
Much of the empirical literature that uses the
CAPM applies beta as a risk measure in order to
adjust asset returns for their degree of riskiness,
prior to the examination of the impact of an
event. 9 For example, beta has been used to adjust returns for risk in numerous event studies
30
dealing with finance issues like judging mutual
fund performance or the price effects of stock
splits and public tender offer announcements.
After rigorous investigation, researchers have
uncovered a number of anomalies that underm i n e the capital asset pricing model. Two of the
more well-known inconsistencies, known initially as the January effect and the small firm effect,
have been particularly damaging. Researchers
have f o u n d that t h e returns to small firms
generally outperform those of larger firms after
a d j u s t m e n t by beta risk measures. In other
research, stocks have shown an abnormally high
excess return after risk adjustment in the month
of January. A study by Donald B. Keim (1983) has
shown that the small firm effect and the January
effect are related; that is, smaller firms outperform larger firms in January. These results con-
"Despite CAPM's simplicity and the
measurability of its variables through
market price data, empirical evidence
has not supported this approach."
tradict implications of t h e CAPM. They have
fueled criticisms of its framework not only as an
equilibrium model of asset pricing but also as a
useful framework for risk adjustment in other
applications.
Recent work by Jay R. Ritter and Navin Chopra
(1989), however, suggests that the capital asset
pricing model's risk-return relationship is more
robust when portfolios weight the individual
assets by their proportion of total market value
in contrast to the standard practice of weighting
assets in a portfolio equally. In those circumstances, small firm effects are deemphasized
and the relationship shows no January seasonal
effects. If nothing else, then, the existence of
anomalies has stimulated additional research
and evidence on the traditional CAPM.
Aside from these empirical shortcomings, the
CAPM is essentially not dynamic. Though the
m o d e l involves n u m e r o u s simplifying condiECONOMIC REVIEW, NOVEMBER/DECEMBER 1989
tions, for this article t h e most relevant assumption is that all investors maximize t h e utility of
terminal wealth. In other words, notwithstanding inevitable uncertainty, future investment
and consumption opportunities are completely
captured by t h e certain m e a n and variance of
the probability distribution of the asset returns.
The CAPM is hence a one-period model that
cannot encompass issues like economic fluctuations and their effects on asset pricing. Fama
(1970) has shown that the CAPM's assumption
about maximizing terminal wealth can b e ext e n d e d to m u l t i p l e periods as long as future
consumption and investment decisions are determined outside t h e m o d e l . However, the implication of Fama's work is that investors have
perfect foresight with regard t o future market
conditions; intertemporal factors like changes
"Recent advances in the sophistication of financial asset pricing theory
have moved to models that address
intertemporal
variations in opportunities over the business cycle."
in economic performance are assumed t o have
already b e e n anticipated a n d thus should not
affect the investment decision. In this sense, the
model is static, although empirical tests estimate the m o d e l as if its restrictions held over
time. Consequently, aside from predicting t h e
return to t h e market portfolio (a difficult task at
best), t h e CAPM as interpreted by Fama d o e s
not p r e s e n t a m e t h o d t o e s t i m a t e any dynamics.
Another controversy in CAPM-based asset
pricing research is whether a truly riskless rate of
return actually exists. Black (1972), in fact, attacks this question by offering a CAPM without
the riskless rate. Generally, though, in empirical
tests, the riskless rate of return, RF, is proxied by
the return on a Treasury bill with o n e m o n t h to
maturity. The return to the market portfolio, RM,
is approximated by s o m e equity index, usually
the Standard and Poor's 500.
Richard Roll (1977) criticizes empirical examinations of the traditional CAPM in what is now
referred to as t h e "Roll critique." His primary
concern is measurement of the market portfolio
in CAPM tests. Roll argues that an u n a m b i g u o u s
test of t h e model cannot b e performed with t h e
typical proxies for market rate of return because
t h e true market portfolio has to include all individual assets. The argument suggests that inferences a b o u t t h e model may b e sensitive to
the composition of the market proxy, and any
demonstrated sensitivity to various reasonable
proxies for t h e market will reduce the testability
of the m o d e l . Robert F. Stambaugh (1982), res p o n d i n g to this criticism, has shown that, although tests are sensitive to the selection of
assets, inferences about the CAPM are insensitive to t h e use of several different proxies for the
market portfolio, suggesting that the CAPM may
b e less sensitive to the Roll critique than t h e
argument implies. Still, Roll's analysis has contributed to deemphasizing the model in m o r e
recent research.
Intertemporal CAPM and
the Consumption CAPM
The ambiguous empirical support for the traditional CAPM as well as dissatisfaction with the
restrictiveness of s o m e of its assumptions has
led researchers toward m o d e l s that relax s o m e
CAPM a s s u m p t i o n s . Recent advances in t h e
sophistication of financial asset pricing theory
have moved to m o d e l s that address intertemporal variations in opportunities over the business cycle. Empirical evidence suggests that the
extension of t h e CAPM to account for intertemporal change is useful. For instance, Katherine
Schipper and Rex Thompson (1981) demonstrated that equity assets may b e used to h e d g e
against changes in consumption and investm e n t opportunities related to unanticipated
shifts in consumption, GNP, a n d the price level,
which serve as proxies for general conditions. 1 0
Robert C. Merton (1973) earlier d e v e l o p e d a
dynamic asset pricing model, drawing from the
initial insights of the mean-variance CAPM b u t
extending the framework to incorporate intertemporal uncertainty. Merton's pricing equation describes a framework that holds in the
II
FEDERAL RESERVE BANK OF ATLANTA
presence of a business cycle. The model allows
investment and consumption opportunities to
fluctuate over time so that the economy's condition is linked directly with asset price behavior.
John B. Long, Jr., (1974) introduced an alternative
dynamic model that specifies relevant variables,
known as "state" variables because they indicate the state of the economy, useful for the
pricing equation. These state variables represent external factors, such as the stock of physical capital, that determine current investment
opportunities. 11 Long's model suggests that
the term structure of interest rates-that is,
interest rates on equally risky d e b t of successively distant maturities—is a key element in
the pricing of equity assets, and recent empirical work has supported this intuition. 12
The general model in Merton (1973) also involves a vector of state variables, which represents the number (S) of relevant variables
n e e d e d to describe the condition of the economy. The state vector indicates whether the
economy is in a recessionary or expansionary
stage of the business cycle and characterizes
uncertainty in a model economy.
The model solution, in the general case, implies that there will b e S + 2 number of portfolios in the equilibrium asset pricing equation.
The additional two portfolios are the market
portfolio and the riskless asset. 13 The resulting
pricing relationship would expand the simple
CAPM to include S additional betas (or sensitivity measures, o n e for each state variable),
and the premia related to each state variable
sensitivity. The general model requires identification of state variables that may b e unobservable, however. Thus, t h e m o d e l may not b e
directly empirically testable with existing econometric methods.
To give more interpretation to the model as
well as to develop a potential route of inquiry,
Merton assumes that the interest-rate movements of the riskless asset are the sole state
variable sufficient to describe the investment
opportunity set. The restricted model provides
a tractable result in which the equilibrium asset
pricing model involves three funds: the market
portfolio, the riskless asset, and a portfolio of
assets negatively correlated with movements in
the riskless asset.
This simplified model presents the intuition
of intertemporal uncertainty more directly than
32
does the general specification. Investors are
compensated for holding both market risk, just
as in the static CAPM, and the risk of unfavorable
movements in investment opportunities as conveyed by the riskless interest rate. In periods of
poor economic opportunities, investors would
1 ike to have assets that offer large returns. In fact,
an investor may h e d g e against aggregate intertemporal risk by holding a risky asset that has an
expected return less than the riskless asset if
the risky asset pays off a high return when the
return to the riskless asset is low.
Although the restricted model in Merton's
work provides insights into the forms of risk presented by shifts in aggregate economic opportunities, the three-fund result remains a special
case. Testing Merton's general model requires
identifying a n d counting t h e state variables.
"/An alternative! model allows investment and consumption
opportunities
to fluctuate over time so that the economy's condition is linked directly with
asset price behavior."
Unfortunately, theory makes no unambiguous
predictions about their number or identity. 14
However, the model motivates investigation of
additional variables as measures of intertemporal risk a n d offers a general structure for
empirical analysis.
The M a c r o e c o n o m i c Link. In an elegant and
influential paper, Douglas T. Breeden (1979)
provides a key link between macroeconomic
growth models and financial models of asset
pricing. This connection makes possible an
analysis of asset price determination in a model
economy that fluctuates over time. Breeden's
construct, which is consistent with Merton's,
shows that the growth rate of consumption is a
sufficient statistic for the state of the economy;
in other words, the S state variables need not b e
identified for asset pricing. The resulting relationship is an equilibrium asset pricing model
that uses the growth rate of (real per capita) conECONOMIC REVIEW, NOVEMBER/DECEMBER 1989
s u m p t i o n as the benchmark return from which
all other assets are priced. 1 5 Thus, covariation
with consumption growth is t h e single relevant
measure of risk. Breeden argues that aggregate
consumption should b e a better proxy for the
desired measure of consumption than the return to a market proxy is for the return t o the
market portfolio. The model is commonly referred to as the consumption CAPM (CCAPM).16
The equilibrium relationship is:
£/ ~Rf=
Pc/
"
*Fh
where £(- is t h e expected return to asset /, RF is
the riskless rate of return, Ec is the expected
growth rate of real per capita consumption, a n d
P c/ is t h e m e a s u r e of t h e covariance of an asset's return with t h e growth rate of consumption.
"Its simplicity as well as its derivation
from a dynamic model has made the
consumption CAPM an attractive method of asset pricing."
By using consumption as the benchmark, the
model is implicitly concerned with fluctuations
in both consumption and investment opportunities. The business-cycle behavior of consumption, therefore, directly affects the pricing
of assets. The intuition b e h i n d this relationship
is that the-marginal utility, or marginal contribution to valuation from an extra unit of consumption, is low in a t i m e p e r i o d that has high
consumption. If consumption fluctuates, a consumer would prefer assets that will h e l p reallocate c o n s u m p t i o n across states t o t h o s e in
which consumption is low. As a result, an asset
return that covaries negatively with consumption growth should h e l p smooth consumption
and b e associated with a negative risk premium.
On the other hand, asset returns that covary
positively with consumption are associated in
this m o d e l with a positive risk premium. Hedging behavior on the part of the investor results
from the incorporation of intertemporal uncertainty into the m o d e l . Persistent differences in
average yields to a selection of assets can b e
explained, therefore, by the insurance that particular assets provide against certain states.
Its simplicity as well as its derivation from a
d y n a m i c m o d e l has m a d e t h e c o n s u m p t i o n
CAPM an attractive m e t h o d of asset pricing. As
with t h e traditional CAPM, the equilibrium relationship of t h e consumption model requires
estimating only o n e parameter to evaluate t h e
risk characteristics of an asset or portfolio. Consumption data are also readily available on a
m o n t h l y basis, so t h e m o d e l can b e t e s t e d
relatively easily. It has b e e n tested often.
A theoretical criticism by Bradford Cornell
(1981) suggests that the consumption m o d e l is
not free of the restrictions implied by Merton's
intertemporal m o d e l ; direct estimation still
requires t h e identification of state variables.
As a result, t h e conditional distribution of cons u m p t i o n betas is random. Although Cornell
notes that this situation may b e resolved with
empirical evidence, t h e theory implies that distribution of the consumption betas relies u p o n
the properties of the state variables. 17
Despite Cornell's criticism, s o m e empirical
research has b e e n d o n e on the adequacy of t h e
consumption CAPM. A recent study by Gregory
N. M a n k i w a n d Matthew D. Shapiro (1986), using
quarterly data from 1959 to 1982, shows that t h e
traditional CAPM outperforms the consumption
CAPM. Based on a large s a m p l e of equity returns, their test employs instrumental variables
estimation methods. 1 8 Its results show that the
expected real return has a significant linear relationship with the market beta b u t not with t h e
consumption beta.
Simon Wheatley (1988) criticizes the inferences m a d e from the Mankiw a n d Shapiro results
because t h e instrumental variables estimations
are widely different from those using t h e ordinary least squares regression technique, suggesting p r o b l e m s with t h e selected estimation
strategy and weakening the resulting inferences. 1 9 Wheatley continues by estimating the
cross-sectional adequacy of the consumption
CAPM restrictions using 40 stock portfolios,
Treasury bills, Treasury bonds, a n d corporate
b o n d s as d e p e n d e n t variables. His tests found
t h e CCAPM implications consistent with t h e
data. 2 0
II
FEDERAL RESERVE BANK OF ATLANTA
To transcend Cornell's criticisms, Breeden,
Michael R. Gibbons, a n d Robert Litzenberger
(1989) used weaker empirical tests of the cons u m p t i o n m o d e l . Their p a p e r e x a m i n e d t h e
CCAPM relative to t h e traditional CAPM using 12
stock portfolios, a Treasury bill asset, a Treasury
b o n d portfolio, a corporate b o n d portfolio, a n d
a junk b o n d p r e m i u m as t h e set of asset returns
to b e explained. Their consumption data are
adjusted for m e a s u r e m e n t p r o b l e m s associated with reported consumption statistics. The
primary p r o b l e m with aggregate consumption
data is that they are issued much less frequently
than observations of stock returns. The CCAPM
theory requires m e a s u r e m e n t of spot consumption growth rates, whereas actual consumption
is measured over an interval. Given the data
adjustments required, empirical evidence found
in support of the m o d e l is necessary, b u t not
sufficient, to accept it.
Nonetheless, Breeden, Gibbons, a n d Litzenberger find that the explanatory power of t h e
consumption growth rate for t h e behavior of
asset returns over t i m e is significant. The results
using t h e return to a portfolio of assets that has
maximum correlation with consumption growth—
the maximum
correlation
portfolio-are
more
c o m p a r a b l e to 1 inear regressions with t h e return
t o a market proxy, since they b o t h use portfolio
returns data as i n d e p e n d e n t variables. Tests of
linearity between consumption beta a n d expected returns reject t h e hypothesis that consumption p a n d expected returns are linearly
related for the full period covered by t h e data.
However, examination of the subperiods suggests that the source of t h e rejection is t h e
period 1929-39, a u n i q u e t i m e in t h e U.S. economy. In all other subperiods, the relationship
c a n n o t b e rejected. Test results imply that
neither t h e maximum correlation portfolio nor
the market portfolio proxy has t h e lowest variance for a given mean return, that is, neither
proxy is mean-variance efficient. Despite these
rejections, t h e estimates for the risk premia
related to consumption a n d to t h e market are
quantitatively similar.
Macroeconomic s t u d i e s that e m b o d y t h e
consumption capital asset pricing model concentrate on t h e relationships between forecasta b l e movements in asset returns a n d in consumption. Lars P. Hansen and Kenneth J. Singleton (1982, 1983) imposed strong assumptions
34
to generate a closed-form solution that would
test t h e predictability of asset returns a n d
obtain estimates of t h e structural parameters of
interest, namely t h e degree of risk aversion a n d
t h e intertemporal discount factor.21 Unfortunately, their empirical results suggest rejection of t h e m o d e l , in part because of p r o b l e m s
associated with measuring consumption data.
However, further work by Sanford J. Grossman,
Angelo Melino, a n d Robert J. Shiller (1987),
which explicitly accounts for t h e t i m e averaging
of c o n s u m p t i o n data, also failed t o s u p p o r t
t h e model. 2 2
In sum, t h e empirical results for the consumption CAPM are mixed. The strong restrictions
i m p o s e d by t h e macroeconomic m o d e l tests
lead to rejection of the m o d e l and d o not prod u c e r e a s o n a b l e or useful e s t i m a t e s of t h e
structural parameters. In contrast, recent evid e n c e on t h e c o n s u m p t i o n CAPM as a relative
asset pricing construct are more hopeful, suggesting s o m e potential for its use in evaluating
asset risk. However, more research is necessary
t o d e t e r m i n e the robustness of the consumption beta measure as a risk gauge for assets; t h e
initial tests are supportive of a linear relationship b e t w e e n consumption risk a n d asset premia b u t d o not s u p p o r t mean-variance efficiency, a prediction of the model. Thus, further
research on the consumption CAPM must b e
d o n e before it can b e widely a p p l i e d .
Arbitrage Pricing Theory
An alternative t o the traditional CAPM paradigm that has gained considerable attention is
arbitrage pricing theory, d e v e l o p e d by S t e p h e n
A. Ross (1976) 2 3 This model retains the distinction between diversifiable a n d nondiversifiable
risk b u t imposes fewer restrictive assumptions
in its derivation of asset returns than d o e s the
CAPM. For e x a m p l e , t h e traditional pricing
m o d e l requires that returns follow the normal
distribution, implying that knowledge of the
m e a n a n d variance is sufficient to describe the
entire distribution. The traditional CAPM relies
on t h e return t o the market portfolio as t h e
benchmark variable that describes asset return
behavior relative to it. In contrast, arbitrage pricing theory d o e s not require normally distribECONOM1C REVIEW, NOVEMBER/DECEMBER 1989
uted returns a n d suggests that a n u m b e r of
variables, known as factors (risk sources), describe asset returns.
the importance of covariance risk in asset pricing as a result of the no-arbitrage assumption,
which has strong theoretical appeal.
The derivation of arbitrage pricing theory
requires two major assumptions. First, agents
are assumed to believe that s o m e identifiable
set of factors generates t h e variabil ity of al 1 asset
returns a n d that their relationship is consistent
across the range of variables. The second assumption is that no opportunities are available
for riskless arbitrage (that is, n o unlimited profits given no net investment). The hypothesized
linear factor model is:
Arbitrage pricing theory is an attractive generalization of the traditional CAPM model's insight that covariance risk—risk that cannot b e
diversified away—underlies t h e pricing of assets. 24 The arbitrage pricing model provides a
c o h e r e n t structure, less restrictive than t h e
CAPM, that allows for investigation of the sources
of risk. The linear factor m o d e l framework, in
addition, appears better a b l e to account for the
anomalies that conflict with the traditional model's predictions. In arbitrage pricing theory, the
covariance is measured relative to t h e factors
that d e t e r m i n e the behavior of asset returns,
whereas the CAPM gauges covariance only relative to the market return. Thus, finding a size factor or a seasonal factor that explains the CAPM
anomalies would seem possible.
where /?, is the uncertain return to asset /, £,- is
the expected return to asset /', bf/- is t h e factor
loading for asset i related to factor j, or asset /"s
sensitivity to movements in factor /', is the factor j {j = 1 . . . k), and 8j is t h e error term for
asset /'. In addition, the m o d e l assumes that the
factors and error terms have a mean of zero. It
d o e s not m a k e other assumptions a b o u t the
distribution of the factors or error terms aside
from requiring that the covariance between the
error terms, e,- a n d e;-, is zero.
In t h e derivation of the traditional capital
asset pricing m o d e l , the "market" m o d e l that
relates all asset returns to movements in the
market return (prior to the pricing equation)
follows directly from the assumption that returns are jointly normally distributed. In arbitrage pricing theory, however, the linear factor
model is an assumption, although the idea that
a set of forces determines the movements of all
asset returns is compelling.
Exact arbitrage pricing implies t h e following
asset pricing relationship:
where A^ is riskless or zero b return a n d
represents risk premia related to factor j. A clear
intuition underlies the equilibrium relation of
arbitrage pricing theory. If the indicated factors
truly generate t h e movements of all asset returns and if current asset prices allow n o riskless
arbitrage, it follows that expected returns are
approximately I ¡nearly related to covariance between the asset returns and the factors. A main
contribution of this theory is that it recognizes
Arbitrage pricing theory has few underlying
a s s u m p t i o n s . It has b e e n criticized, though,
because its initial form has few rejectable hypotheses. Refuting the theory itself, which d o e s
not identify or limit the n u m b e r of factors, is difficult. 2 5 Thus, tests of t h e arbitrage pricing
theory are c o m b i n e d examinations of the pricing relationship a n d the appropriateness of the
set of factors chosen. 2 6 Theoretical extensions
a n d refinements by a n u m b e r of researchers
have provided the foundation for the substantial a m o u n t of empirical research that has b e e n
produced and the many works that are still in
progress. 27
Empirical m e t h o d s d e v e l o p e d to i m p l e m e n t
estimation of the factors a n d factor loadings in
arbitrage pricing theory have involved two distinct a p p r o a c h e s t o t h e d a t a : factor analytic
techniques (or principal c o m p o n e n t analysis as
in the work of Gregory Connor a n d Robert A.
Korajczyk (1988|) a n d prespecification of the factors. 28 The former m e t h o d employs the estim a t e d covariance matrix of returns to determ i n e the factor structure that underlies asset
return behavior. 2 9 Estimates of the factors are
d e t e r m i n e d in accordance with arbitrage pricing theory; that is, factors are estimated from t h e
characteristics observed in the set of returns.
The second technique attempts to identify factors w i t h o u t first examining t h e structure of
returns. Instead, variables are chosen as n e e d e d
by economic intuition that these factors affect
II
FEDERAL RESERVE BANK OF ATLANTA
asset pricing. The m e t h o d uses t h e prespecified factors to estimate factor loadings a n d then
tests to see if t h e loadings are associated with
significant risk premia. 3 0
This article will survey only the m o s t recent of
the large n u m b e r of papers on arbitrage pricing
theory. 31 Two recent works c o m p a r e this theory
with the traditional CAPM approach as m o d e l s
of asset pricing. 32 Bruce N. L e h m a n n a n d David
M. M o d e s t (1988) cannot reject the arbitragebased construct when asset portfolios are formed
on the basis of dividend yield or an asset's own
return variance. Since CAPM research has found
an anomaly with regard t o d i v i d e n d yield a n d
asset pricing, the evidence can b e viewed as
supportive of the arbitrage pricing theory as
an alternative.
O n t h e other hand, t h e researchers reject t h e
arbitrage pricing m o d e l when t h e portfolios are
formed on the basis of firm size. Connor a n d
Korajczyk (1988) show evidence consistent with
Lehmann a n d Modest that a significant relationship exists between firm size a n d asset expected return that is not captured by the arbitrage
pricing theory. However, Connor a n d Korajczyk
demonstrate that t h e size effect is separate
from a seasonal effect (for example, the January
effect), which appears to b e explained by the
variation in t h e risk factors. 33
K.C. Chan, Nai-fu Chen, a n d David A. Hsieh
(1985) a n d Chen, Roll, and Ross (1986) e m p l o y
prespecified factors in testing t h e arbitrage
pricing theory predictions. In b o t h works, t h e
theory shows n o significant anomalous behavior
related t o firm size. 34 Since t h e two empirical
methodologies are q u i t e different, t h e conflicting evidence suggests that more research is
n e e d e d to investigate t h e issue.
In sum, arbitrage pricing theory represents a
generalization of t h e CAPM intuition that covariance risk forms a basis for asset pricing. The
arbitrage m o d e l makes few assumptions in its
derivation a n d provides a m e t h o d to investigate
the underlying sources of asset risk. This theory
has shortcomings, however, especially with regard t o t h e n u m b e r a n d t h e identity of t h e
underlying risk factors a n d empirical testing.
The factor structure has b e e n estimated in different ways, although t h e techniques that estim a t e this structure from t h e e s t i m a t e d covariance matrix of asset returns seem most consistent with the theoretical model.
36
The current status of arbitrage pricing theory
testing suggests its consistency with the data,
although the m o d e l cannot explain the anomalous firm size effect. However, t h e capital asset
pricing m o d e l cannot account for that anomaly,
either. Thus, a m o n g static m o d e l s , arbitrage
pricing theory seems to b e a viable alternative
to t h e CAPM.
Dynamic Models
Although theoretical extensions of both paradigms have extended t h e basic m o d e l to an
intertemporal realm in search of a productive
way to link pervasive economic factors t o equity
market performance, b o t h arbitrage pricing
theory a n d t h e capital asset pricing m o d e l
e m p l o y the fiction of a single period m o d e l . 3 5
The linkage between macroeconomic and financial markets has also b e e n explored within a
dynamic general equilibrium m o d e l , notably by
William A. Brock (1980, 1982), a n d |ohn C. Cox,
Jonathan E. Ingersoll, Jr., a n d Ross (1985), in
which asset prices are e n d o g e n o u s functions of
underlying economic forces. However, t h e empirical implications of these m o d e l s are not
directly testable.
Brock provides a key link to understanding
the relationship between t h e static and intertemporal models, a n d h e emphasizes the degree of generality in t h e m o d e l s that generate
t h e testable implications. The Merton pricing
m o d e l , for example, introduced intertemporal
aspects to t h e traditional m o d e l , b u t Merton s is
a partial equilibrium construct. The state variables that d e t e r m i n e intertemporal asset price
movements are not linked to the underlying
sources of uncertainty in t h e economy. Brock, on
t h e other hand, derives a general equilibrium
m o d e l in which the state variables—here, technological factors underlying economic uncertainty—determine behavior of asset prices. The
model provides o n e interpretation of technological shocks as the arbitrage pricing theory
factors presented in Ross (1976), b u t it may also
apply to Merton's m o d e l , or Long's (1974). In an
example, Brock shows that t h e Sharpe-Lintner
capital asset pricing m o d e l conforms to the case
of o n e underlying technological shock. As a
further exposition, t h e Brock m o d e l has t h e
ECONOMIC REVIEW, NOVEMBER/DECEMBER 1989
characteristic of consumption sufficiency—as in
the Breeden model—so that the c o n s u m p t i o n
CAPM m o d e l holds. Thus, Brock presents a
framework in which all major asset pricing models may b e derived a n d provides a unifying syst e m to motivate research linking macroeconomic factors and asset price behavior.
Empirical research on arbitrage pricing theory
that employs prespecified factors to estimate
factor l o a d i n g s relates closely to t h e macrofinance implications of the Brock as well as the
Cox, Ingersoll, a n d Ross models. In fact, Chen,
Roll, and Ross use these more general m o d e l s
on which to b a s e their empirical investigation.
As m e n t i o n e d above, t h e m e t h o d appears to
stretch the arbitrage pricing theory's motivation
of t h e determination of factor structure, yet they
address the issue of the factors' identity. The
motivation of linking the real economy with asset returns and the freedom to choose factors a
priori has produced s o m e stimulating empirical research.
Chan, Chen, and Hsieh (1985) investigated the
firm size effect by prespecifying factors in a multifactor pricing equation, in which the factors are
measures of economic and financial activity that
may relate to asset pricing. They include the
market portfolio, industrial p r o d u c t i o n , two
estimates of inflation, the change in the term
structure, and the risk premium. The results
show that the observed firm size effect has a
strong relationship with t h e risk premium measure (the difference between t h e yield on lowrated long-term b o n d s a n d t h e yield t o a
portfolio of long-term government bonds). The
variation in t h e risk premium reflects alterations
in business conditions and, therefore, introduces an intertemporal feature into the empirical asset pricing m o d e l . These results imply that
the firm size effect may b e captured by the multifactor asset pricing m o d e l . Also, the firm size
effect may b e consistent with an efficient market
in which small firms have higher expected returns because of higher risk that is not captured
by the traditional CAPM model's risk measures.
S u b s e q u e n t empirical work by Chen, Roll,
and Ross investigated directly t h e role of economic forces in asset pricing, using similar econ o m i c variables as t h e prespecified factors.
They found similar evidence that t h e multifactor
model explains t h e pricing of a selection of
asset portfolios formed on the basis of firm size.
The authors s h a p e d the selection of economic
state variable proxies by choosing those that
influence either cash flows to firms or t h e discount rate a p p l i e d to asset cash flows in the simple stock valuation m o d e l .
The formulation of prespecified factors in
these studies assumes that the chosen variables constitute t h e factor structure of asset
returns, which is the underlying determinant of
asset return time variation. The research d o e s
not present time-series evidence to suggest
that these factors explain much of the timeseries variability of asset returns. In factor
analytic research, time-series explanatory power
is evident in t h e m e t h o d of identifying factors. In
future research on economic factors and asset
pricing, the time-series regressions of the prespecified factors will b e useful indicators of
whether t h e chosen factors are relevant. 36
The underlying shocks (or factors) in Brock
and Cox, Ingersoll, and Ross represent technological shocks that directly affect the productivity of t h e economy. Yet the main explanatory
variables in these studies are financial measures, notably the term structure proxy and t h e
risk p r e m i u m proxy. These variables are at least
partially determined by the true underlying factors, just as asset prices are. Although financial
factors have significant implications for the pricing of risky assets and provide insights into the
interrelationships of macroeconomic and financial markets, the results d o not reveal the underlying sources of uncertainty.
The search for these underlying sources may
seem futile. However, recent studies by David
Alan Aschauer (1989a, b) suggest that governm e n t s p e n d i n g behavior, primarily changes in
t h e public capital stock, may b e o n e source of
uncertainty which directly affects the aggregate
productivity of the economy. In his 1989 paper,
this researcher shows that the government stock
of infrastructure capital—for example, roads,
buildings, sewers, and so on—has a significant
i m p a c t on t h e profitability of t h e aggregate
economy. In other words, t h e p u b l i c capital
stock has a positive effect on t h e aggregate
value of private firms. Thus, further work on asset pricing should investigate the effects of government policy, since these shocks seem most
justifiably to b e exogenous variables. 3 7 Research in this area may also provide economic
policymakers with better information a b o u t the
II
FEDERAL RESERVE BANK OF ATLANTA
long-term effects of s p e n d i n g policies at all
levels of government.
Conclusion
Recent financial models of asset pricing derive from the initial insights into the relative
riskiness of different assets and the trade-off
between risk and expected return provided by
the traditional capital asset pricing model. The
various models surveyed here provide a coherent framework in which to analyze asset
returns. Over time, the CAPM has b e e n useful for
portfolio evaluation and for extending scientific
analysis of financial markets. It continues to b e
used as a method to evaluate the risk of assets
or portfolios. The model requires only one estimable parameter per firm or portfolio. However,
the CAPM's static framework, the difficulty of
predicting the return to the market proxy, evid e n c e in conflict with its implications, a n d
theoretical advances in financial modeling have
combined to shift attention away from the simple CAPM as an equilibrium model of asset pricing. The consumption-based asset pricing model
(CCAPM) presents a dynamic construct in which
a single estimable parameter measures asset
risk. This model has m e t criticism on matters of
data measurement and inconclusive empirical
evidence of its usefulness. Recent work nonetheless presents some support for further research in this area.
The intertemporal CAPM and arbitrage pricing theory, though clearly different models, suffer similar empirical difficulties. Neither provides insights into the identity of the multiple
sources of asset risk. For arbitrage pricing
theory, empirical a p p l i c a t i o n s using factor
analysis cannot interpret risk sources. However,
the two models provide a motivation for investigating multiple sources of asset risk.
Ongoing theoretical d e v e l o p m e n t s p o i n t
toward future research that can link economic
factors to asset pricing behavior. Such research
should interest investors and especially policymakers, who may gain insight into the effects of
alternative economic policies. For the policymaker, an appreciation of the risk sources in the
economy can aid formulation of policy by linking
information provided by equity market behavior
to real economic performance. In addition,
further research may uncover elements of economic policy as sources of macroeconomic uncertainty and provide policymakers with an
improved set of policy guides.
Notes
1
tribution remains t h e m o s t c o m m o n a p p r o x i m a t i o n of t h e
In fact, as e v i d e n c e of their influence, financial asset pric-
distribution of stock returns.
ing theories have p e n e t r a t e d Wall Street a n d are currently
b e i n g u s e d in t h e design of m u t u a l fund portfolios.
2
T h e traditional capital asset pricing m o d e l remains, how-
5
S e e also Treynor (1961).
6
T h e traditional CAPM involves several a d d i t i o n a l assumptions that m a y b e f o u n d in S h a r p e (1985) or other fi-
ever, a useful m e t h o d t o analyze asset characteristics with
n a n c e textbooks.
few measures.
7
Black ( 1972) presents a m o d e l without a riskless asset that
3
This uncertainty is larger in s o m e periods than in others.
4
D e s p i t e e v i d e n c e that stock returns a p p e a r leptokurtic
offers predictions that are m o r e consistent with t h e Black,
("fat-tailed," or having a higher probability t h a n a normal
Jensen, a n d Scholes results.
distribution of observing extreme values), the normal dis-
38
ECONOMIC REVIEW, NOVEMBER/DECEMBER 1989
8
9
Levy (1978) suggests that if individuals are not well diver-
t h e highest return. Roll's (1977) critique suggests that this
sified their own variance of return s h o u l d b e relevant for
implication has not b e e n tested a d e q u a t e l y . For arbitrage
asset pricing.
pricing theory, a portfolio that has only risk related t o t h e
For a n intuitive discussion of event study m e t h o d o l o g y
f u n d a m e n t a l factors is mean-variance efficient. This as-
s e e Hunter a n d Walker (1988).
p e c t of the m o d e l has b e e n tested empirically in several
I(>
27
cific m o d e l .
1
studies.
rhe results, however, d o not represent a test of any spe-
S e e , for example, H u b e r m a n (1982), C h a m b e r l a i n a n d
' O n e may interpret these state variables to b e virtually
R o t h s c h i l d (1983), a n d C o n n o r (1984). S e e H u b e r m a n
anything: t h e weather, oil s u p p l y shocks, m e a s u r e s of
g o v e r n m e n t policy, a n d s o o n . As will b e d i s c u s s e d
,2
1
(1986) for a m o r e exhaustive list of references.
28
Factor analysis is a statistical procedure in which "com-
further, t h e identity of such variables is subject to con-
m o n factors" are u n o b s e r v a b l e hypothetical variables that
siderable debate.
c o n t r i b u t e t o t h e v a r i a n c e of a vector of d e p e n d e n t
S e e results in Chan, C h e n , a n d Hsieh (1985); Chen, Roll,
variables. That is, factor analysis is a m e t h o d t o d e s c r i b e
a n d Ross (1986); a n d McElroy a n d Burmeister (1988).
t h e variation of a set of variables without explicit ex-
^The m o d e l has also b e e n referred to as the m u l t i b e t a
planatory variables. A data series, then, will b e d e s c r i b e d
CAPM, in which an e s t i m a t e d parameter is associated with
as a linear f u n c t i o n of a set of c o m m o n factors a n d o n e
each state variable.
u n i q u e factor that contributes variance only t o that series.
T h e p r o b l e m , however, is not u n i q u e to Merton's m o d e l ,
In the set of d e p e n d e n t variables, each variable has o n e
,4
15
as t h e discussion of arbitrage pricing theory indicates.
u n i q u e factor that is uncorrelated with all other u n i q u e
O n e c o u l d also use the asset portfolio that has m a x i m u m
factors. The coefficients, or factor loadings, for each comm o n factor provide t h e e s t i m a t e s of b¡ in the APT.
correlation with the growth rate in c o n s u m p t i o n as t h e
29
benchmark.
l6
S e e also R u b e n s t e i n (1976) a n d B r e e d e n a n d
A l t h o u g h factor analysis is m o r e efficient, the compu-
Litzen-
tational d e m a n d s of t h e m e t h o d limit the n u m b e r of
berger (1978).
l7
S e e Cornell (1981) for technical e l e m e n t s a n d t h e com-
returns that can b e analyzed at o n e time.
30
H u b e r m a n (1986) suggests that this form of research, relat-
p l e t e argument. Bergman (1985) criticizes t h e a s s u m p t i o n
ing e x p e c t e d return t o covariances of asset returns with
of time-separable preferences in t h e derivation of t h e
other variables, is m o r e in line with the Merton intertem-
CCAPM. This a s s u m p t i o n i m p l i e s that past decisions o n
poral CAPM. Below, t h e Brock m o d e l is u s e d t o show t h e
c o n s u m p t i o n d o n o t affect today's choices. W i t h o u t the
a s s u m p t i o n , t h e Merton ICAPM still holds, b u t it can n o
similarity of the two m o d e l s .
3
' S o m e references for t h e earlier yet important works are
longer b e c o l l a p s e d into t h e CCAPM. D e s p i t e this prob-
(1983), a n d Dhrymes et al. (1985). S e e H u b e r m a n (1986) for
time-sepa'rable preferences a n d that t h e CCAPM holds.
a m o r e extensive listing.
' i n s t r u m e n t a l variables e s t i m a t i o n m e t h o d s use variables
19
20
Roll a n d Ross (1980), Brown a n d Weinstein (1983), C h e n
lem, m o s t m a c r o e c o n o m i c m o d e l s a s s u m e that there are
32
L e h m a n n a n d M o d e s t (1988) use factor analytic tech-
correlated with t h e regressors b u t unrelated t o t h e errors
n i q u e s o n 750 asset returns to isolate a factor structure.
in an a t t e m p t to r e d u c e t h e potential correlation be-
Then they test t h e APT with t h e s e factors o n a selection of
tween regression variables a n d t h e residual error.
asset portfolios, g r o u p e d o n t h e basis of d i v i d e n d yield,
Wheatley suggests that either t h e instruments are weakly
an asset's own return variance, a n d firm size. C o n n o r a n d
related to t h e underlying variables of interest or that t h e
Korajczyk (1988) e s t i m a t e factors using asymptotic prin-
u n d e r l y i n g v a r i a b l e s a r e c o l l i n e a r . In e i t h e r case, t h e
cipal c o m p o n e n t s , which allows m o r e returns in t h e
results in M a n k i w a n d S h a p i r o (1986) are suspect.
estimation of t h e covariance matrix. The asset portfolios
A l t h o u g h t h e results d o n o t suggest r e j e c t i o n of t h e
u s e d as d e p e n d e n t variables are g r o u p e d o n the basis
of size.
CCAPM, t h e e s t i m a t e of t h e relative risk aversion parameter greatly exceeds t h e theoretical value.
2
33
B o t h p a p e r s reject t h e restriction of m e a n variance ef-
34
T h e research that uses prespecified factors to test APT will
ficiency in APT as well as in t h e CAPM.
' T h e a s s u m p t i o n s are (1) joint log-normality of asset returns a n d c o n s u m p t i o n growth a n d (2) a constant relative
22
risk aversion specification of utility.
b e e x a m i n e d further b e l o w in the discussion of mac-
S i n c e t h e test a s s u m e s b o t h constant relative risk aver-
roeconomic factors a n d asset pricing.
sion utility a n d joint log-normality of returns a n d con-
S e e O h l s o n a n d G a r m a n (1980) a n d Connor a n d Korajczyk
(1988) for discussions of intertemporal arbitrage pricing
b e t h e source of t h e m o d e l failure. Further work may b e
theories.
r e q u i r e d in t h i s area t o d e c i p h e r t h e i m p l i c a t i o n s of
t h e results.
23
35
s u m p t i o n growth, the violation of either restriction could
The intertemporal CAPM, CAPM, a n d a recent intertemporal m o d e l in Cox, Ingersoll, a n d Ross (1985) have m u c h
For a m o r e d e t a i l e d survey of t h e APT, s e e H u b e r m a n
in c o m m o n with m o d e r n dynamic macroeconomic m o d e l s
(1986).
(stochastic growth models) such as t h o s e of Lucas (1978)
24
S e e S h a r p e (1985): 199-200.
a n d Brock (1982). These similarities i n c l u d e the key role of
25
S e e S h a n k e n (1982, 1985) a n d the r e s p o n s e by Dybvig a n d
t h e real interest rate, concern for the changing investment
Ross (1985).
a n d c o n s u m p t i o n o p p o r t u n i t i e s faced by c o n s u m e r s , a n d
26
T h e m o d e l implications can b e e x t e n d e d to the c o n c e p t
t h e attention to e c o n o m i c forces as the underlying sour-
of mean-variance efficiency. In t h e CAPM, t h e m o d e l
ces of asset risk p r e m i a . The progress in m o d e l i n g a
i m p l i e s that t h e market portfolio is mean-variance effi-
d y n a m i c e c o n o m y with an asset market has occurred in
cient; that is, given its level of risk, t h e market portfol io has
b o t h fields; empirical work on t h e issue has n u m e r o u s
II
FEDERAL RESERVE BANK OF ATLANTA
potential applications. It is notable, however, t h a t only
(1986) in a nonlinear e s t i m a t i o n m e t h o d that presents
t h e ICAPM a t t e m p t s t o i s o l a t e u n d e r l y i n g e c o n o m i c
b o t h time-series a n d cross-sectional pricing results of t h e
variables—that is, state variables-directly; t h e c o n s u m p -
multifactor m o d e l . Their results generally s u p p o r t t h e
tion CAPM is similar t o t h e traditional CAPM in the u s e of a
usefulness of t h e e c o n o m i c variables in explaining b o t h
types of variation.
reference portfolio t o price assets relative t o that port37
folio.
36
M c E l r o y a n d Burmeister (1988) e m p l o y v a r i a b l e s s i m i l a r t o
Chan, C h e n , a n d Hsieh (1985) a n d C h e n , Roll, a n d Ross
R e s e a r c h by Tallman (forthcoming) investigates t h e effects of g o v e r n m e n t s p e n d i n g behavior o n cross-sectional
asset pricing m o r e in t h e tradition of financial research.
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II
FEDERAL RESERVE BANK OF ATLANTA
U.S. and Foreign
Direct Investment Patterns
William ). Kahley
Since 1985, when this Bank's Economic Review last surveyed foreign direct investment,
foreign ownership of plants, real estate, and the
like in the United States has grown considerably
in importance and magnitude. The 1985 article
reported: "Many Americans are unaware t h a t . . .
international activities wield a sizable a n d
steadily growing impact u p o n t h e economic
characteristics of the region and the nation." In
the meantime both American awareness and
direct foreign investment have m a d e significant
gains. This article draws on newly available data
to u p d a t e the status of foreign direct investment in the United States and the Southeast. It
also probes some economic impacts of foreign
direct investment, focusing particularly on
employment and exports.
A wide variety of observers, from policymakers to small business owners, are now interested in investments that foreigners make in the
U.S. economy. As the magnitude of investment
by Europeans, Asians, and others rose in the
1980s, public concern over such foreign investment accelerated, intensifying the d e m a n d for
The author
Atlanta
is an economist
Fed's Research
for extensive
42
research
in the regional
Department.
assistance.
section
He thanks Amy
of
the
Bailey
information on the subject. Accounts of billiondollar acquisitions of major U.S. corporations by
foreigners often relayed fears that control of corporate America may b e slipping out of domestic
hands. O p i n i o n polls have shown that t h e
American public is troubled by the increased
foreign ownership of U.S. firms a n d real estate.
In contrast, government officials and other
opinion leaders in southeastern states have displayed a generally positive perspective on foreign direct investment. The Southeast receives
an especially large share of foreign companies'
spending on new plant and equipment. Political
and business leaders have come to appreciate
t h e jobs, tax base, a n d diversification that
foreign direct investment can bring.
Many workers also welcome the foreign presence. In 1987 the number of Americans employed in foreign-owned U.S. affiliates was 3.2
mill ion. More than one out of eight of these jobs
were in the Southeast, defined in this article as
the states in the Sixth Federal Reserve District:
Alabama, Florida, Georgia, Louisiana, Mississippi, and Tennessee. Today, southeastern employees working for foreign-owned U.S. affiliates probably number close to half a million.
U.S. ownership of plants abroad generally
predates foreigners' direct investments in busiECONOMIC REVIEW, NOVEMBER/DECEMBER 1989
nesses here. The major expansion in U.S. direct
investment overseas took place in the 1950s
and 1960s, whereas international investments
in the United States have b e e n especially fastgrowing only since the 1970s. Just as many
Americans now oppose foreign direct investm e n t here, critics have faulted U.S. corporations' decisions to produce outside the United
States, chiefly claiming that millions of American workers' jobs are lost in the process. For
their part, U.S. multinational corporations have
argued that their direct foreign presence is
n e e d e d to serve foreign markets adequately
and that customers in the United States benefit
from lower prices on imported goods produced
at lower-cost foreign subsidiaries.
Based on available data and information, it is
impossible to estimate accurately the net economic impact on this country of U.S. companies'
foreign investment activities or of foreign direct
investment here. However, the ever-expanding
amount of research on the topic suggests that
both types of flows probably increase U.S. production and well-being. From a theoretical
perspective, most economists and policymakers
accept the view that international capital flows
help companies make better use of the world's
resources. This result occurs because foreign
investment presumably increases competition
in an industry through the entry of new companies. Seeking a competitive edge, firms in an
industry try to cut costs, improve efficiency, or
enhance product quality to maintain or expand
market share. Ultimately, consumers should
benefit from a lower-priced or higher-quality
product that economizes on resource usage.
This same theoretical perspective also implies that the flow of capital across national borders benefits workers and company owners. If
the resources are complementary, employees
should b e better off because the availability of
foreign capital raises labor productivity; consequently, wages should rise or the number of
employed workers should increase. The availability of foreign capital also should reduce the
cost of capital, making some plant investment
projects cheaper and boosting t h e value of
firms, thus benefiting their owners and stimulating investment. On the other hand, domestic
savers and financial intermediaries may b e losers
in the short run as a consequence of greater
capital availability. Savers could lose interest
income because of lower interest rates brought
about by the a d d e d supply of capital, while
entry of foreign lenders could increase competition in the financial lending business and reduce profitability or the rate of return.
This article presents available information on
t h e magnitude, industrial distribution, and
geographic concentration of foreign investment
in the United States generally and in the Southeast. 1 Along with a discussion of alternative
measures of investment and conceptual and
statistical p r o b l e m s associated with these
measures, the article compares features of investment in the United States by "U.S. affiliates"
of foreign c o m p a n i e s with U.S. corporations'
investment in "foreign affiliates." The discussion next makes tentative assessments of some
impacts of foreign investment in the United
States, with particular attention to two questions:
• How, if at all, have job growth and worker
income been influenced by foreign investment?
• How, if at all, has foreign investment stimulated U.S. exports?
The final portion of the article focuses on the
importance of foreign direct investment in the
Southeast. The article concludes with a discussion of emerging trends and prospects for foreign investment in t h e nation a n d by U.S.
companies during the 1990s.
The Activities of U.S. and
Foreign Affiliates
Overall Activity. A statistical snapshot of inward and outward foreign investment for the
United States at year's end 1987 reveals some
important information. As measured by employment, U.S. multinationals were more active,
with 6.2 million workers employed in their foreign affiliates compared to 3.2 million workers
in U.S. affiliates of foreign c o m p a n i e s (see
Table I).
In contrast, less reliable data on book values
of assets suggest that the magnitude of foreignowned operations in the United States is much
closer to that of U.S.-owned operations abroad.
The book value of foreign corporations' U.S.
II
FEDERAL RESERVE BANK OF ATLANTA
The M e a n i n g a n d M e a s u r e m e n t of Foreign Investment
U.S. statistics-gathering agencies define foreign
direct investment in the United States and U.S.
investment abroad as ownership or controldirectly or indirectly—of 10 percent or more of an
enterprise's voting securities, or an equivalent
interest by an individual, partnership, group, or
organization. Businesses under such control are
called affiliates, and the investment is said to be
direct. Although another type of foreign investment in a private enterprise, known as portfolio
investment, refers to the purchase of stocks or
bonds by investors seeking to diversify their
assets rather than exercise an effective management role, the terms foreign direct investment and
foreign investment are used interchangeably
throughout the rest of this article.1 In addition, the
term multinational corporation is used to refer to
all foreign investors even though some actually are
individuals or other entities.
There are several ways to measure the magnitude and importance of foreign investment. Conceptually, the best measure of importance is
annual value added, or contribution to final output. However, value-added data are not available
for foreign affiliates, and other measures that only
approximate the importance or contribution of
foreign investment activity must be used as proxies to compare inward and outward foreign investment.2 This article focuses on employment
and the gross book value of property, plant, and
equipment. These complementary gauges lend
themselves to calculations of national and regional levels, shares, and growth rates by industry and
by country (of origin or destination). Thus, these
data serve as proxies for the stock, or cumulative
value, of foreign investment and as measures of
importance and change in such activity.
Although employment and gross book value
data tend to be correlated, or move together, their
patterns of change can vary. Therefore, these data
series are not equally suited for all purposes. For
example, gross book value data do not serve as
reliable measures of growth in real industrial
activity because they are valued at (constant)
acquisition cost. Market value would be better,
with values for all years adjusted by prices for
some base year. Also, an acquired firm may revalue its assets from historical book value to fair
market value, thus changing the asset valuation
while employment and the value of production
remain static. Thus, data on the number of jobs or
employment associated with foreign investment
are better for measuring growth in foreign investment activity. On the other hand, the gross book
value may be more accurate than employment
figures in measuring industrial or regional shares if
foreign investment is in capital-intensive industries and industries in which capital has been substituted for labor. Even then, gross book value
comparisons are only approximations because of
the shortcomings noted. Generally, when the
amount of capital used per worker varies from
industry to industry, the industrial and regional
shares and patterns of change vary. The form that
foreign investment takes can also make a difference in terms of its impact. For example, if a
merger or acquisition merely involves the purchase of existing assets, the transfer of ownership
may generate few or no new jobs. By contrast, capital inflows to build and equip new plants generate
new jobs immediately.
Foreign investment activities can be classified
according to type and characteristics:
• acquisitions and mergers of enterprises whereby title to stock or assets of a business are
secured by a foreign investor;
• a rise in percentage ownership by a foreign
investor, known as equity increases;
• joint ventures, in which two or more entities
establish a new business according to contractual provisions; and
• new plants and plant expansions, or a foreign
investor's establishment of a new operating
facility or addition to existing capacity.
Notes
1
O t h e r m a j o r c o m p o n e n t s of foreign investment in t h e
United States i n c l u d e foreign official assets in t h e
2
V a l u e - a d d e d e s t i m a t e s are available for U.S. affiliates
at t h e national level for the 1977-86 period. A com-
United States, such as their h o l d i n g s of U.S. Treasury
parison of the value a d d e d a n d e m p l o y m e n t d a t a for
securities, a n d U.S. b a n k liabilities. O t h e r major U.S.
t h e s e firms for 1986 shows that manufacturing affili-
investment assets a b r o a d i n c l u d e U.S. official reserve
ates' e m p l o y m e n t share of all affiliate e m p l o y m e n t ,
assets, U.S. g o v e r n m e n t loans, a n d U.S. b a n k claims. In
47 percent, was a b o u t t h e s a m e as their share of all
1987 foreign direct investment totaled 26 percent of all
affiliates' v a l u e a d d e d , 45 percent. Value a d d e d a n d
U.S. assets a b r o a d a n d 17 percent of foreign-owned
e m p l o y m e n t s h a r e s varied w i d e l y for o t h e r indus-
assets in t h e United States.
tries.
44
ECONOMIC REVIEW, NOVEMBER/DECEMBER 1989
Table 1.
Selected Data for U.S. and Foreign Affiliates, 1987
Millions of Dollars
Number of
Employees
Total
Assets
Annual
Sales
Annual Employee
Compensation
Foreign Affiliates
of U.S. Corporations
6,234,600
1,098,166
1,052,260
134,715
U.S. Affiliates
of Foreign Corporations
3,159,700
926,042
731,392
93,652
Sources: See U.S. Department of Commerce, Bureau of Economic Analysis (1989a, b, c).
affiliates' property, plant, and e q u i p m e n t was
$926 billion in 1987 compared to $1,098 billion
for foreign affiliates of U.S. companies. However,
U.S. investments abroad are on average much
older than foreign-owned investments in the
United States and were m a d e when asset prices
were far lower. Comparing the magnitude of
activity using book values of assets exaggerates
the foreign presence in the United States compared to U.S. multinationals' activities abroad.
In 1987 both sales and employee compensation
of foreign affiliates of U.S. companies substantially exceeded those of U.S. affiliates of foreign
companies. These differences also suggest that
U.S. outward investment exceeds inward investment.
These employment numbers and income and
asset values seem large, but they appear less so
when compared to the total national economy.
In 1987, employment of foreign multinationals'
U.S. affiliates accounted for 3.6 percent of the
86.6 million workers in n o n b a n k U . S . businesses, according to a survey conducted by the U.S.
Commerce Department's Bureau of Economic
Analysis. 2 This presence d o u b l e d the 1.8 percent share recorded in 1977.
Although the overall percentage of workers
employed by U.S. affiliates remains small, these
shares are significantly larger for some industries. For example, U.S. manufacturing affiliates
employed over 7 percent of all U.S. manufacturing workers and accounted for nearly half of the
employment by U.S. affiliates in 1987. (Partly
because foreign investment is concentrated in
chemicals and other industries with relatively
low employment-to-assets ratios, U.S. affiliates'
12 percent share of manufacturing assets was
larger than the employment share.) Based on
available information that shows foreign investment still growing at a fast pace, U.S. affiliates'
share in manufacturing employment and assets
may well b e larger today.
Foreign a n d U.S. Characteristics. Foreign direct investment here and U.S. firms' direct
investments abroad have distinct characteristics. Sources and applications of such investments shown in Tables 2 and 3 display these
differences.
The geographic pattern of U.S. direct investm e n t a b r o a d is m o r e d i s p e r s e d than is t h e
pattern of country sources of foreigners' investments here. Foreign affiliates located in industrialized countries accounted for a b o u t
70 percent of employment in U.S.-owned enterprises abroad in 1987, while Canada, Japan, and
the European nations accounted for almost 90
percent of employment in all foreign-owned
U.S. affiliates.
O n e of the more noticeable features of foreign investment in the United States over the
past decade has been the growing prominence
of Japan as a major foreign investor. Between
1977 and 1987 Japan's share of U.S. affiliate
employment rose from 6 percent to 9 percent,
and its share of assets among U.S. affiliates' rose
from 4 percent to 21 percent. Based on 1987
data, Japan ranks first in terms of assets and
fourth in terms of employment. However, the
relatively recent vintage of Japanese investment
may overstate the value of its assets vis-a-vis
countries that have long been investing in factories and real estate. Japan also ranks higher by
the asset measure than the employment measure because of Japanese investors' acquisiII
FEDERAL RESERVE BANK OF ATLANTA
Table 2.
Shares of Assets and Employment
for U.S. and Foreign Affiliates by Country, 1987
Employment
Assets
U.S. Companies'
Foreign Affiliates
Foreign Companies'
U.S. Affiliates
U.S. Companies'
Foreign Affiliates
Foreign Companies'
U.S. Affiliates
Canada
14.6
18.7
13.8
15.2
Europe
France
Germany
Netherlands
Switzerland
United Kingdom
41.2
5.7
8.9
2.1
0.8
12.8
60.2
5.8
11.5
8.5
5.8
19.9
48.0
4.3
8.3
4.6
3.4
15.7
50.5
3.7
6.3
7.6
9.0
16.9
Japan
5.5
9.0
9.7
21.1
Australia, New Zealand,
and South Africa
7.2
4.0
4.3
3.0
19.7
4.5
14.7
3.5
Middle East
1.6
1.0
2.2
1.9
Other Africa, Asia,
and Pacific
9.7
1.4
6.1
2.1
Latin America
Sources: See U.S. Department of Commerce, Bureau of Economic Analysis (1989b, c).
tions of financial companies, which are assetintensive.
By industry, manufacturing accounted for 65
percent of foreign affiliates' e m p l o y m e n t in
1987 but "only" 48 percent of foreign companies' U.S. affiliates' workers were in the factory sector. Retail trade accounted for a much
higher share of U.S. affiliate employment, and
finance was a much bigger component of U.S.
affiliates' assets. Foreigners, particularly from
other d e v e l o p e d countries, a p p e a r strongly
attracted both to the large and affluent U.S. consumer market—with its efficient distribution
network—and to its financial services industry.
Some other noteworthy contrasts (not shown
in the accompanying tables) appear when comparing these investment shares. As might b e
expected on the basis of differences in country
wealth, nations like Italy, Spain, Brazil, Mexico,
and many in Asia and the Pacific are more likely
to host U.S. investment than to have companies
with large interests in the United States. In addition, U.S. foreign investments in developing
countries, where wage rates are lower, make
considerable use of labor, whereas activity in
46
advanced countries tends to b e in more capitalintensive industries.
C o m p a r i n g Foreign a n d U.S. Patterns. More
detailed analysis of foreign investment data can
help determine whether the investment patterns of U.S. and foreign multinational corporations are similar or different. Table 4 shows
concentration ratios for manufacturing industries. These ratios are c o m p u t e d by dividing
each industry's share of total affiliate employm e n t by t h e overall U.S. share in t h e s a m e
industry. An industryvaluegreaterthan o n e suggests a preference for the industry.
Foreign investment in the United States is concentrated in resource-intensive manufacturing
industries, whereas U.S. investment abroad appears to b e concentrated in technology-intensive
industries. Specifically, U.S. firms' foreign affiliates' concentration ratios exceed o n e for chemicals; nonelectrical, electronic, and electrical
machinery; transportation equipment; instruments; a n d rubber a n d plastic products. Of
these industries, all but rubber can b e classified
as technology-intensive. By contrast, in addition
to their concentration in chemicals, foreign comECONOMIC REVIEW, NOVEMBER/DECEMBER 1989
Table 3.
Shares of Assets and Employment
for U.S. and Foreign Affiliates by Industry, 1987
Employment
Assets
U.S. Companies' Foreign Companies' U.S. Companies' Foreign Companies'
Foreign Affiliates
U.S. Affiliates
Foreign Affiliates
U.S. Affiliates
Mining
1.6
0.8
1.4
Petroleum
4.7
3.7
17.9
8.7
65.4
6.5
9.3
4.2
19.3
26.1
48.0
4.6
12.2
5.0
10.2
16.0
38.8
3.2
8.1
2.4
10.4
14.7
23.6
2.5
8.2
2.5
3.5
7.0
Wholesale trade
7.9
9.9
9.1
10.5
Retail trade
8.7
18.0
1.4
2.9
Finance, except banking,
insurance, and real estate
2.5
6.5
26.0
48.0
Agriculture
1.5
0.4
0.2
0.3
Manufacturing
Food and kindred products
Chemicals and allied products
Primary and fabricated metals
Machinery
Other
1.3
Construction
0.8
1.3
0.4
0.4
Transportation,
communication, and utilities
1.4
2.9
1.8
1.0
Services
5.6
8.5
2.9
3.2
Sources: See U.S. Department of Commerce, Bureau of Economic Analysis (1989b, c).
panies' U.S. affiliates have e m p l o y m e n t concentrations in s t o n e , clay, a n d glass products; primary metals; and petroleum and c o a l industries that are basically resource-intensive.
Impacts of Foreign Investment
O n e would h o p e that foreign investment, like
domestic investment, promotes economic
growth, enhances productivity, a n d bolsters the
competitiveness of U.S. industry. Newspaper
accounts have reported anecdotally on s o m e
successes of individual foreign investments,
such as the revival of m o r i b u n d U.S. tire companies a n d the reinvigoration of parts of the
a u t o m o b i l e manufacturing industry. 3 Besides
bringing in new money a n d possibly increasing
net investment and growth, foreign investors
also have introduced new technology, such as
process engineering, improved quality control
FEDERAL RESERVE BANK OF ATLANTA
m e t h o d s , a n d a c q u a i n t e d m a n a g e m e n t with
innovative approaches, such as just-in-time inventory systems and quality circles.
Unfortunately, these impacts of foreign investment cannot b e quantified systematically.
Determining precisely how many U.S. workers'
jobs are attributable to foreign investment is
not even possible, although direct investment
in manufacturing has u n d o u b t e d l y a d d e d jobs
in s o m e industries and kept j o b losses down
in others. 4
E m p l o y m e n t impacts are concentrated in
manufacturing since U.S. affiliate employment
is concentrated there (see Table 2). Among individual manufacturing industries, U.S. affiliates' shares are above total U.S. shares except in
textiles, apparel, lumber, furniture and fixtures,
rubber, and transportation e q u i p m e n t .
U.S. affiliates appear to b e good employers.
Compensation per worker at U.S. affiliates inc r e a s e d at an above-average rate in m o s t
manufacturing industries compared tocompenII
Table 4.
Concentration Ratios for Manufacturing Assets and Sales
of U.S. and Foreign Affiliates, 1986*
Concentration Ratio for Assets
Concentration Ratio for Sales
Foreign Companies' U.S. Companies' Foreign Companies' U.S. Companies'
U.S Affiliates
Foreign Affiliates
U.S Affiliates
Foreign Affiliates
Chemicals and allied products
Stone, clay, and glass products
Primary metal
Petroleum and coal
Printing and publishing
2.69
1.89
1.70
1.24
0.97
1.95
0.40
0.80
1.01
0.10
2.98
2.05
1.92
1.38
0.81
1.93
0.34
0.56
1.85
0.11
Electrical and
electronic equipment
Food and kindred products
Paper and allied products
Fabricated metal
Instruments and related products
0.94
0.79
0.67
0.63
0.53
1.28
0.73
0.84
0.77
1.30
1.19
0.69
0.72
0.64
0.58
1.17
0.69
0.74
0.60
1.25
Machinery, except electrical
Textile products
Rubber and plastics products
Transportation equipment
Other
0.46
0.37
0.33
0.24
0.46
1.51
0.44
1.40
1.55
0.89
0.62
0.34
0.37
0.35
0.33
1.75
0.24
1.08
1.70
0.55
* Concentration
businesses
ratios
in an
are affiliate
export
shares
of industry
sales
divided
by comparable
export
shares
for all
U.S.
industry.
Sources: See Howenstine (1988): 59-75, and U.S. Department of Commerce, Bureau of Economic Analysis (1988a, b).
sation increases for all firms in the s a m e industries in the 1977-86 period. Moreover, affiliate
compensation per worker was in 1977 already
higher in a majority of manufacturing industries,
including t h e i m p o r t a n t c h e m i c a l s industry.
Compensation per worker for affiliates was also
higher in 1986 in every other major e m p l o y m e n t
category (see Table 5) c o m p a r e d t o average
compensation for all U.S. firms in those industries. However, between 1977 and 1986 compensation per worker grew more slowly in U.S.
affiliates than for all U.S. firms in retail trade,
agriculture, transportation, communication and
utilities, and services, narrowing compensation
differentials, though they still favor affiliates.
It is tempting to infer from t h e foregoing information that foreign investment has improved
the c o m p e n s a t i o n of workers at U.S. affiliates
compared to all workers in the s a m e industry.
However, this conclusion m u s t b e q u a l i f i e d .
Previous research by the author has shown that
foreign direct investment in the United States
tends to b e attracted t o industries p o p u l a t e d
48
by large firms; other researchers have established that such firms t e n d to pay higher wages
a n d offer greater fringe benefits for workers with
the s a m e skills, experience, and occupations.
W h e n adjusted for these factors, t h e higher a n d
faster-growing worker compensation observed
for U.S. affiliates p r o b a b l y reflects firm a n d
industry size differences in the mix of affiliate
versus domestic firms.5 This finding is consistent
with an earlier analysis by the U.S. Commerce
D e p a r t m e n t ' s Bureau of Economic Analysis.
That u n p u b l i s h e d study, based on 1980 data
covering hourly wages of production workers at
U.S. affiliates a n d all businesses in an industry,
concluded that there was n o evidence that industrial wage rates for U.S. affiliates a n d all
businesses were different. Also, the U.S. General Accounting Office has compared wages for
employees of U.S. affiliates a n d U.S. automakers
a n d has concluded that wages received were
c o m p a r a b l e for t h e two groups.
Proponents of foreign investment often assert that it p r o m o t e s exports. As a start to
ECONOMIC REVIEW, NOVEMBER/DECEMBER 1989
Table 5.
Employee Compensation per Worker
for U.S. Affiliates and All U.S. Businesses by Industry, 1986
Annual Employee Compensation per Worker
Foreign Companies' U.S. Affiliates
1986
Mining
Percent
Change
1977-86
Total U.S.
1986
Percent
Change
1977-86
1986 Ratio of
Compensation by U.S.
Affiliates to Compensation
by all Employers
$42,849
144.0
$28,899
74.3
148.3
Manufacturing
33,513
106.5
24,441
78.7
137.1
Wholesale trade
32,656
97.0
24,147
75.5
135.2
Retail trade
13,602
37.7
10,988
57.3
123.8
Finance, insurance,
and real estate
50,643
227.1
24,857
108.7
203.7
Agriculture
15,949
26.7
13,819
58.7
115.4
Construction
29,855
122.6
22,430
48.4
133.1
Transportation,
communication,
and utilities
32,213
64.4
26,150
71.9
123.2
Services
18,655
73.0
16,627
81.0
112.2
Sources: See U.S. Department of Commerce, Bureau of the Census (1981, 1988) and U.S. Department of Commerce, Bureau of
Economic Analysis (1985, 1988a).
analyzing this assertion, o n e should answer two
questions: are U.S. affiliates concentrated in
industries that tend to export, and d o e s foreign
investment s t i m u l a t e exports within a given
industry?
The answer to t h e first question is "probably
not." In t h e American manufacturing sector,
nonelectrical machinery, instruments, transportation e q u i p m e n t , a n d chemicals are the only
industries for which exports amount to 10 percent
or more of the value of U.S. sales (see Table 6). Of
these industries, foreign investment is concentrated only in chemicals, and, as the concentrations depicted in the last column of Table 6
show, U.S. affiliates of foreign chemical companies are less likely to export than are domestic chemical companies.
Industries in which U.S. affiliates had aboveaverage ratios of exports to sales in 1986 relative
to all U.S. firms in that s a m e industry included
only primary metals, printing a n d publishing,
and petroleum a n d coal. Overall, U.S. manufacturing affiliates were less likely to export than
were U.S.-owned manufacturing firms in 1977
and 1986, and thus the boost to U.S. exports
supposedly given by affiliates may not exist.
Moreover, t h e concentration ratios suggest that
affiliate manufacturers t e n d e d to b e less likely
to export in 1986 than they were in 1977 compared to their domestic counterparts. 6
Explanations for these export patterns are
not immediately apparent. However, if foreign
companies are attracted to producing in the
United States primarily to gain access to t h e U.S.
market, affiliate manufacturers might b e less
likely to export than U.S.-owned manufacturers.
Ad hoc explanations for the particular industries' tendencies probably exist also. Unfortunately, lack of detailed information about the
ownership and product composition of affiliates
in the various industries precludes discussion
of such explanations here.
The foregoing analysis suggests that job and
worker income growth may have benefited from
foreign direct investment. On the other hand,
U.S. affiliates' export-generating benefits d o not
appear positive compared to those for domestic producers.
II
FEDERAL RESERVE BANK OF ATLANTA
Table 6.
Exports of U.S. Affiliates and All U.S. Manufacturing Industries
(shares of sales, in percent)
Foreign Companies'
U.S. Affiliates
Manufacturing
Concentration Ratios
Total U.S.
1977
1986
1977
1986
1977
1986
5.3
5.7
6.5
7.2
0.83
0.80
1.20
0.72
1.68
1.51
0.58
0.87
1.38
0.95
4.5
6.1
5.6
8.7
2.0
8.8
5.5
4.3
3.5
8.4
3.4
5.7
3.5
10.2
4.0
4.5
15.5
7.4
11.9
2.4
9.9
4.2
4.2
1.5
16.0
8.0
4.6
1.4
16.1
9.4
5.4
1.2
0.97
0.93
2.59
1.69
0.62
0.98
0.77
1.29
Rubber and plastics products
Stone, clay, and glass products
Transportation equipment
Instruments and related products
1.9
1.7
9.0
9.1
3.3
0.8
10.0
7.5
4.3
3.1
11.0
14.0
4.9
2.9
11.2
13.5
0.43
0.56
0.81
0.66
0.67
0.26
0.89
0.56
Petroleum and coal*
Other (textile, tobacco, leather,
apparel, lumber and furniture
products, and miscellaneous)
4.0
3.7
0.7
1.4
5.82
2.70
12.6
6.1
5.2
5.5
2.41
1.11
Food and kindred products
Chemicals and allied products
Primary metals
Fabricated metals
Machinery except electrical
Electrical and electronic equipment
Paper and allied products
Printing and publishing
* U.S. affiliates'
category
exports
in total U.S.
in the petroleum
category
are assumed
to correspond
to the petroleum
and coal
products
exports.
Sources: See U.S. Department of Commerce, Bureau of the Census (1981, 1988) and U.S. Department of Commerce, Bureau of
Economic Analysis (1985,1988a).
Foreign Investment in the Southeast
Foreign investment's impact in the Southeast
also interests analysts and others: Where have
the investments b e e n m a d e , a n d in what industry? What are the impacts of such activity? As
with t h e nation, t h e task of describing where
investment has occurred in t h e region is fairly
s i m p l e compared to gauging its economic impacts. Nevertheless, previous analysis by t h e
author of factors motivating foreigners to invest
in particular industries a n d geographic areas
has generated s o m e information to help understand t h e regional impacts of this activity.
From these studies of the region, o n e can conclude that the Southeast has attracted an especially hefty share of such investment and that
the region's lures have b e e n favorable business
a n d meteorological climates, above-average
economic growth, and plentiful profit oppor-
50
tunities, owing in part to the availability of lowcost resources such as labor a n d energy. 7
Comparing aspects of foreign investment in
the region with foreign investment nationally
using e m p l o y m e n t data for t h e 1977-87 period
confirms the special favor t h e Southeast enjoys
with foreign investors. Employment growth for
all U.S. affiliates d u r i n g this 10-year s p a n was
159 percent, yet regional affiliate e m p l o y m e n t
growth was 239 percent (see Table 7). This disparity was a b o u t as large as the e m p l o y m e n t
growth difference between the region a n d the
nation over the s a m e period. The fast-paced
growth of U.S. affiliate e m p l o y m e n t e n a b l e d the
region's share of total U.S. affiliate e m p l o y m e n t
t o rise from 10 percent in 1977 t o m o r e than
13 percent 10 years later.
If regional a n d national growth rates of U.S.
affiliates are compared using b o o k values of
assets, a somewhat different a n d surprising picture is revealed. The nation displays si ightly fastECONOMIC REVIEW, NOVEMBER/DECEMBER 1989
er growth over the 1977-87 period: 418 percent
compared to 378 percent for the region. The disparity between e m p l o y m e n t and asset-value
comparisons may b e related to differences in
the industry mix of foreign investment at the
national and regional levels.
The region's foreign investment differs from
the nation's in other ways. To a greater extent
than in t h e United States as a whole, foreign
investment in t h e S o u t h e a s t has t e n d e d t o
entail building new manufacturing plants and
boosting employment-intensive service sector
industries such as wholesale a n d retail trade.
Fifteen percent of t h e value of foreign investment in the Southeast in 1986 was for new plants,
compared to less than 6 percent in the nation. 8
Merger and acquisition investments, often involving large capital-intensive U.S. companies,
accounted for 61 percent of foreign investment
in the region a n d 63 percent in the nation.
The region continues to b e an active host to
foreign investment in a wide spectrum of industries and from investors all around the globe. A
relatively high share of direct investment in the
Southeast has taken the form of new construction in nontraditional industries.
Between 1977 and 1987 affiliate e m p l o y m e n t
growth in t h e region e x c e e d e d c o m p a r a b l e
growth rates for t h e nation in all industries
except chemicals a n d real estate. In the chemical industry, regional a n d national growth rates
were e q u a l . In real estate, national affiliate
employment growth was more than one-third
faster than affiliate growth in t h e region (see
Table 8). Employment shares within the region
changed somewhat during this span. The biggest shifts b e t w e e n 1977 a n d 1986 were a decline in manufacturing's share of affiliate employment to 45 percent from 60 percent in 1977,
a rise in retail trade's share from 9 percent to 18
percent, a n d a rise in the share of other services
to 12 percent (from just 0.1 percent). For asset
values, industrial affiliate shares within t h e
region shifted similarly.
Reliable data are not available to summarize
the impact of e m p l o y m e n t and asset shifts on
regional worker compensation levels or on diversifying the southeastern economy. However,
growth of foreign investor interest in t h e region clearly has shifted toward employmentintensive industries such as services and retail
trade. If regional shifts in affiliate versus total
Table 7.
U.S. Affiliate Employment
and Growth, 1977-87
Total Affiliate Employment
Amount
Alabama
Florida
Georgia
Louisiana
Mississippi
Tennessee
Southeast
United States
- Percent
Change
1977
1987
14,313
28,250
30,693
18,367
5,734
26,215
35,100
116,800
117,700
50,800
17,600
80,700
145.2
313.5
283.5
176.6
206.9
207.8
123,572
418,700
238.8
1,218,711
3,159,700
159.3
Sources: See U.S. Department of Commerce, Bureau of Economic Analysis (1985, 1989c).
compensation levels by industry followed the
national pattern in the 1977-87 period, s o m e
relative shift p r o b a b l y occurred o u t of t h e
generally higher-paying jobs in capital-intensive
industries and other manufacturing jobs into
lower-paying service sector jobs. However, this
shift may also have hastened growth in affiliate
e m p l o y m e n t because the service sector is more
labor-intensive.
Differences in national and regional growth
rates of employment and assets by industry
caused a fewsignificant shifts in the Southeast's
industry concentration ratios in t h e 1977-86
period. Most importantly, t h e region's concentration in chemicals disappeared, while specialties developed in metals, machinery, and
"other" manufacturing industries. In services, an
above-average concentration emerged in retail
trade, reflecting t h e especially fast growth of t h e
southeastern market. Shifts in concentration of
b o o k values of industry assets showed similar
patterns of change.
In 1987 t h e regional affiliate employment distribution by country of origin of foreign direct
investment in the Southeast was similar t o the
nation's (see Table 9). Latin American and Midd l e East investors favored the Southeast relative to the rest of the country. Though Japanese
investment is often regarded as more widespread in the Southeast than elsewhere, in fact
t h e concentration of Japanese investment is
less in the region than in the nation. However,
II
FEDERAL RESERVE BANK OF ATLANTA
Table 8.
Foreign Companies' U.S. Affiliate
Employment and Growth by Industry, 1977-87
Southeast
United States
Percentage
Change in
Employment,
1977-87
Employment
Share, 1987
(in percent)
Employment
Share, 1987
(in percent)
Percentage
Change in
Employment,
1977-87
0.9
88.7
Mining
0.6
Petroleum
4.1
169.5
3.9
35.7
45.2
3.9
10.3
5.1
11.2
12.9
153.9
175.5
92.2
208.5
215.4
215.6
44.3
5.1
12.0
4.9
10.3
12.0
104.1
124.3
91.8
81.2
103.3
122.2
7.9
145.5
9.6
99.1
20.5
665.5
18.3
307.7
Finance
0.6
770.8
1.7
446.0
Insurance
2.6
371.2
2.3
122.3
Real estate
1.6
243.0
1.1
330.8
11.7
351.3
100.0
159.3
Manufacturing
Food
Chemicals
Metals
Machinery
Other
Wholesale trade
Retail trade
Other
12.4
Total
100.0
Components
individual
do not add to totals because
—
—
238.8
some
firms. The effect of data suppression
Also, meaningful
calculation
of percentage
detailed
data are not published
may be to lower the calculated
changes
in employment
to prevent
shares
in mining
disclosure
for the Southeast
and other industries
of information
on
in a few
instances.
was not
possible.
Sources: See U.S. Department of Commerce, Bureau of Economic Analysis (1985,1989c).
Japan's southeastern presence has grown rapidly from a substantial base. Japanese affiliates'
e m p l o y m e n t has e x p a n d e d at a b o u t two times
t h e national pace. Assets and sales of Japanese
companies' U.S. affiliates have also grown at a
substantially faster rate than comparable indicators for other U.S. trading partners. By year's
e n d 1987 m o r e t h a n o n e j o b o u t of ten at
Japanese U.S. subsidiaries was in this region. 9
The major shifts in t h e Southeast's affiliate
shares by country of origin in the 1977-87 period
included sharp increases in e m p l o y m e n t shares
for C a n a d a , Japan, Australia, New Z e a l a n d ,
South Africa, and t h e M i d d l e East, and a drop in
share and concentration for Latin America. The
latter is u n d o u b t e d l y related to d e b t p r o b l e m s
in Latin American countries.
Industry and country-of-origin specializations
are, of course, linked; for example, European
52
chemical producers own chemical plants across
the region. Similarly, t h e Southeast has b e e n a
favorite place for foreign ownership of agricultural land (see Table 10). Much of that ownership
is in the region's vast forests, and several of the
biggest foreign owners are headquartered in
Canada. Currently, Japanese investment interest in Florida citrus c r o p l a n d a n d A l a b a m a
ranchland is growing, and Japanese activity in
t h e a u t o m o b i l e assembly and parts supplying
industries is large, particularly in Tennessee.
Emerging Trends and
Future Prospects
As shown in this article, foreign investment
patterns are exerting a discernible influence on
ECONOMIC REVIEW, NOVEMBER/DECEMBER 1989
Table 9.
Foreign Companies' U.S. Affiliate Employment by Country, 1987
Southeast
Number of
Employees
Canada
United States
Employment
Share
(in percent)
Number of
Employees
Employment
Share
(in percent)
Southeast
Share
of U.S.
Southeast
Concentration
Ratio
85,500
20.4
590,500
18.7
14.5
1.09
234,100
25,800
30,600
39,300
17,300
82,800
55.9
6.2
7.3
9.4
4.1
19.8
1,903,700
183,600
363,300
269,500
183,400
630,100
60.2
5.8
11.5
8.5
5.8
19.9
12.3
14.1
8.4
14.6
9.4
13.1
0.93
1.06
0.64
1.10
0.71
0.99
Japan
29,300
7.0
284,600
9.0
10.3
0.78
Other Asia and Pacific
19,500
4.7
149,500
4.7
13.0
0.98
Latin America
34,400
8.2
143,600
4.5
24.0
1.81
16.0
1.21
Total Europe
France
Germany
Netherlands
Switzerland
United Kingdom
Middle East
5,200
1.2
32,500
1.0
Africa
1,900
0.5
19,900
0.6
9.5
0.72
United States
3,800
0.9
35,500
1.1
10.7
0.81
418,700
100.0
3,159,700
100.0
13.3
All Countries
Components
The effect
do not add to totals because
of data suppression
some detailed
may be to lower
data are not published
the calculated
shares
to prevent
for the Southeast
—
disclosure
on individual
in a few
instances.
firms.
Source: See U.S. Department of Commerce, Bureau of Economic Analysis (1989c).
the e c o n o m i c l a n d s c a p e of t h e nation a n d t h e
S o u t h e a s t , e v e n if their i m p a c t is n o t easily
specified. T h e current t r e n d toward globalization of markets suggests that multinational corporations will b e as p r o m i n e n t d u r i n g t h e 1990s
Table 10.
Land Owned and Mineral Rights
Leased or Owned
by Foreigners, 1987
as in t h e d e c a d e n o w concluding. T h e con-
(thousands
of acres)
ditions that have drawn foreign investment t o
the S o u t h e a s t d o n o t s e e m to b e d i s a p p e a r i n g .
Foreign investors c o m i n g to t h e United States
Acres of
Land Owned
will p r o b a b l y c o n t i n u e t o favor t h i s region.
However, several t r e n d s are e m e r g i n g
that
might dramatically affect future investment flows
from a b r o a d t o t h e U n i t e d S t a t e s a n d
the
Southeast, a n d vice versa.
The S o u t h e a s t has b e e n a large a n d fastgrowing s e g m e n t of t h e U.S. market. This has
h e l p e d draw foreign c o m p a n i e s as they have
l o o k e d to l o c a t e s u b s i d i a r y p l a n t s . Foreign
investors w h o have b u i l t n e w p l a n t s in t h e re-
Alabama
Florida
Georgia
Louisiana
Mississippi
Tennessee
Southeast
United States
Acres of
Mineral Rights
Leased or
Owned
625
893
709
720
369
108
405
737
70
889
593
98
3,424
2,792
13,829
42,531
gion as well as governors of southeastern states
(who participate in t h e g r o u n d b r e a k i n g cerem o n i e s for m a n y of t h e s e plants) have pro-
Source: See U.S. Department of Commerce, Bureau of Economic Analysis (1989c).
II
FEDERAL RESERVE BANK OF ATLANTA
claimed the importance of regional growth in
attracting investment to the region.
Future Foreign Investment. Several international economic and political developments
suggest that inward and outward foreign investment will continue to grow in the 1990s.
• The six-year-old Caribbean Basin Initiative
was d e s i g n e d to h e l p Caribbean nations
d e v e l o p their e c o n o m i e s by giving t h e m
duty-free access to the U.S. market and to
encourage American businesses to invest in
that region. Now, most U.S. firms can benefit
from low labor costs there by operating subsidiaries in the region and exporting to the
United States duty-free. Although the apparel industry is excluded from favorable
treatment, the very low cost of labor and the
requirement to pay duty only on the value
a d d e d abroad has encouraged growing numbers of U.S. apparel manufacturers to establish operations in the Basin.
• The Mexican government a n n o u n c e d in May
a liberalization of its direct investment regulations that will permit total foreign ownership of companies with assets of up to $100
million. Mexican officials also promised to
remove most restrictions on foreign investm e n t in t h e tourist industry a n d to give
foreign investors access to previously restricted sectors such as glass, cement, iron, steel,
and cellulose.
foreigners, the standardization brought about
by the initiative will enable U.S. companies to
operate more freely and efficiently, thereby
reducing their production and distribution
costs. Removal of geographic barriers will
lower transportation costs and encourage
d e v e l o p m e n t of pan-European marketing
efforts, while eliminating technical barriers
via uniform regulations and standards should
enable companies to reap economies of scale
in production.
• S o m e other countries also have a strong
potential for absorbing U.S. foreign investment. South Korea, like Mexico, is liberalizing
its investment regulations, although majority
Korean ownership will still b e required in
technologically advanced industries a n d
others d e e m e d critical (such as those which
involve large imports of raw materials for
processing with a high value a d d e d ) and
defense-related industries. Other developing countries in Asia, Africa, and Latin America
offer investment opportunities as well, as d o
some of the socialist countries, including the
Soviet Union under its current policy of openness and reform.
• The U.S.-Canada Free Trade Agreement,
which took effect at the beginning of this year,
will phase out all tariffs between the United
States and Canada over the next 10 years;
ensure "national" treatment so that U.S. and
Canadian businesses are free of discriminatory laws at the state, provincial, or municipal level; and loosen Canadian restrictions on U.S. investment. The agreement is
likely to boost growth in Canada and spur U.S.
investment there.
Foreign multinationals' interest in acquiring
or establishing American operations also is likely
to continue to b e strong. Numerous large foreign companies d o not yet have a strong direct
presence here. Some may want to buy or develop U.S. enterprises that can improve their
global market positions. Besides wanting to
augment their manufacturing capability, foreign
multinationals also are seeking access to new
technology and operations that complement
existing product lines or furnish a well-known
brand n a m e . U.S. a n d foreign firms also are
likely to enter into more partnerships and temporary deals that will increase foreign investment in the United States. All of these factors
suggest that the amount of foreign investment is
likely to remain high through the next decade.
• The phenomenon that has come to b e known
as Europe 1992 will result in a single European Community (EC) market which will replace a dozen separate national markets. The
EC now boasts 320 million p e o p l e with production capacity about equal to that of the
United States. If the EC market stays open to
Foreign investment in the Southeast, in addition to having grown rapidly, has expanded and
matured in interesting directions. Geographically, nonmetropolitan areas have increasingly
b e e n affected. More and more second-tier companies, especially among Japanese firms, have
recently been established to supply larger firms
54
ECONOMIC REVIEW, NOVEMBER/DECEMBER 1989
with facilities here or to carve out i n d e p e n d e n t
market niches. At the same time growing trade,
transportation, and investment linkages between the Southeast and countries around the
world are creating new investment opportunities in a broad array of industries.
Even though southeastern states will probably keep benefiting from foreign investment,
surveys of affiliate managers have revealed
several issues of concern, some of which relate
to regional shortcomings. For example, the accounting firm Peat Marwick annually compiles
data on foreign-based companies with U.S.
headquarters in Georgia. 10 Responses before
1988 identified the lack of quality education in
Georgia as o n e of the top two concerns. (In some
instances this problem was perceived by the
Peat Marwick authors to b e one of image rather
than a situation that actually required attention.) Moreover, inadequate labor quality and
availability has moved u p in importance as a
major concern in recent years.
Beyond p o s s i b l e regional drawbacks lie a
host of country-specific and some broader inter-
national influences that could restrain growth. 11
Protectionist legislation, the tax environment,
and the availability of investor incentive programs, for example, are factors of major concern
to foreign investors.
Summary
The world economy is in the midst of a direct
foreign investment surge. Outlays by foreign
investors to acquire or establish U.S. businesses
have risen sharply since 1977 and are now producing at record rates. Large foreign multinational corporations are seeking to expand
and diversify in world markets, including especially the large, fast-growing, and stable U.S.
economy. The Southeast has captured an aboveaverage share of foreign investment, particularly
for new plants and activities. Newly developing
investment opportunities in the United States
and abroad suggest that the globalization process will continue in the 1990s.
Foreign Investment from the Southeast
Just how active internationally are companies
headquartered in the Southeast? According to
data compiled by the Conference Board, large
manufacturing companies based in Alabama,
Florida, Georgia, Louisiana, Mississippi, and Tennessee with activities abroad had about $33.4 billion in total sales and $5.4 billion in foreign sales in
1987. Regional companies with foreign investments and with sales greater than $100 million
numbered only 32, or about 3.2 percent of all large
U.S. multinational corporations. Among the southeastern states, Florida was home to the greatest
number of these multinational manufacturersjust 12 firms compared to 150 headquartered in
California.
Based on these data, southeastern companies
do not appear especially active internationally visa-vis the rest of the nation. However, the size distribution of manufacturing firms in the Southeast
compared to the rest of the nation is unknown; the
region may simply not be the headquarters for
many large companies. Moreover, the region could
be home to a significant number of companies
that are active internationally, but which are small
or medium-sized firms.
Although 32 large southeastern-based manufacturing companies hold investments abroad,
they do not necessarily have foreign plants. The
data showthat the region's multinationals own 967
principal U.S. plants yet only 82 foreign plants.
Many of the firms may hold licensing agreements
with host country companies or simply have sales
and service departments abroad.
In general, the southeastern multinationals,
which are distributed all over the world, tend to be
concentrated in technology-intensive industries.
This pattern stands in contrast to foreign investors
in the region. These seem to be predominantly
European, Canadian, or Japanese and tend to
specialize in the resource-intensive industries. A
state-by-state summation of activity abroad is presented below.
Alabama. Four companies headquartered in
Alabama are active internationally. These four
firms have made investments abroad in the clothing and apparel, machinery, electronics, industrial
II
FEDERAL RESERVE BANK OF ATLANTA
chemicals, concrete, and plastic products industries. Only one owns foreign plants—one in Singapore and one in the United Kingdom.
Florida. All but one of Florida's 12 multinational
firms have plants abroad. One manufacturer of
general industrial machinery and equipment, as
well as optical instruments and lenses, maintains
the highest number of foreign facilities, with
plants in Belgium, Canada, France, Ireland, and
theUnited Kingdom. Florida's other multinational
firms chiefly produce various types of machinery
and equipment, electronics, plastics products,
and fabricated rubber. The two most common
sites for investment seem to be Canada and the
United Kingdom.
Georgia. Georgia has the second highest count
of multinationals (10), but the largest foreign sales
among the region's states. In 1987, multinational
corporations headquartered in Georgia earned
about $20.3 billion in sales, or three-fifths of total
sales by regional multinationals. The Coca-Cola
Company, with over half its $7.7 billion sales from
foreign markets, has an encompassing global
presence. The corporation owns at least 19 foreign
plants. Its closest state rival in terms of foreign
facilities is a manufacturer of fabrics and carpets
with 13 foreign plants in five countries. Popular
countries for foreign investment by Georgia's multinationals are Canada, the United Kingdom, and
the Dominican Republic.
Louisiana. With only two companies maintaining foreign affiliates, Louisiana hosts the second
least number of internationally active firms among
the states in the region. Two companies produce
construction machinery and equipment and build
and repair ships and boats. These two companies
have a total of nine foreign plants in Singapore, the
United Kingdom, Canada, Egypt, Indonesia, Nigeria, and the United Arab Emirates.
Mississippi. Mississippi appears to be the least
active internationally of the southeastern states.
In 1987 the state was not credited as home to any
large multinational. However, one company, described as the world's largest sound-systems
manufacturer, is an example of a smaller-sized
firm with international activities. The company
operates 17 facilities in the state, as well as a video
production studio in Los Angeles, and owns subsidiaries in Canada, England, and the Netherlands.
Tennessee. Tennessee, like Alabama, has a
total of four large firms with investments abroad
and just two foreign plants among them. The
plants are located in Canada and Mexico. The
companies are involved in a variety of industries,
including machinery and equipment, household
furniture, drugs, detergents and cosmetics, and
miscellaneous apparel and wood products. Worldwide sales are about $1.1 billion, or just 3.4 percent of total regional multinational sales.
Notes
'Discussion of t h e motivations for foreign direct invest-
TWO excellent articles in this vein a p p e a r e d recently in t h e
York Times
(see Hicks, "The Takeover of American
New
m e n t motivations are related to e x p e c t e d return, risk, a n d
Industry" a n d "Foreign Owners Are Shaking u p t h e Com-
information considerations. Moreover, certain e c o n o m i c
p e t i t i o n , " May 28, 1989). T h e s e articles d e s c r i b e h o w
a n d political forces may h e l p explain longer-run global
foreign c o m p a n i e s have altered t h e c o m p e t i t i v e dynam-
t r e n d s in t h e types a n d a m o u n t s of foreign investment
ics in industries such as chemicals, b u i l d i n g materials,
activity while s o m e other factors influence t h e precise tim-
tires, a u t o m o b i l e s , a n d steel.
ing, geographic location a m o n g a n d within countries, a n d
2
3
m e n t is b e y o n d the s c o p e of this article. Generally, invest-
4
W h e t h e r or not there is a net e m p l o y m e n t gain d e p e n d s
industrial patterns of investment. For d e t a i l e d discussion
u p o n t h e e x t e n t t o which U.S. affiliates r e p l a c e U.S.
of t h e s e issues s e e U.S. D e p a r t m e n t of C o m m e r c e (1984)
imports (or h o m e country exports) c o m p a r e d t o U.S. jobs
a n d Kahley (1987).
lost or d i s p l a c e d b e c a u s e of increased c o m p e t i t i o n or
T h e Federal Reserve System regularly collects asset a n d
b e c a u s e foreign firms' affiliates use m o r e capital at the
b a l a n c e s h e e t data o n t h e b a n k i n g industry and, t o avoid
e x p e n s e of labor relative t o practices of d o m e s t i c U.S.
redundancy, t h e U.S. D e p a r t m e n t of C o m m e r c e a n n u a l
surveys d o not collect data o n banks. However, t h e Fed
d o e s not collect e m p l o y m e n t data for banks.
56
firms.
^ h e r e also are s o m e technical p r o b l e m s in c o m p a r i n g
affiliate e m p l o y m e n t a n d total U.S. e m p l o y m e n t . At t h e
ECONOMIC REVIEW, NOVEMBER/DECEMBER 1989
d e t a i l e d industry level, c o m p a r i s o n s of e m p l o y m e n t may
8
not b e a p p r o p r i a t e b e c a u s e of differences in industry
by t h e U.S. C o m m e r c e D e p a r t m e n t ' s International Trade
classification b e t w e e n U.S. affiliate a n d all U.S. business
Administration.
e m p l o y m e n t d a t a . T h e affiliate d a t a are classified by
9
industry at t h e enterprise or c o m p a n y level, whereas total
were o p e r a t i n g in the Southeast at t h e b e g i n n i n g of 1989,
m e n t level; consequently, affiliate a n d all industry com-
e m p l o y i n g over 41,000 workers. The a m o u n t of Japanese
pensation levels could also b e affected by an "industry
investment in t h e region (excluding Louisiana) at that t i m e
mix" effect. In a d d i t i o n , U.S. affiliate c o m p e n s a t i o n inc l u d e s any p a y m e n t s t o workers d u r i n g the year, while
l0
1
total U.S. e m p l o y m e n t a n d compensation are as of March.
7
was e s t i m a t e d at nearly $5 billion.
e m p l o y m e n t is as of the e n d of t h e year, a n d t h e data for
T h e statistical finding that U.S. affiliates' likelihood of
D a t a c o m p i l e d by t h e C o n s u l a t e G e n e r a l of J a p a n in
Atlanta s h o w that 496 lapan-affiliated e s t a b l i s h m e n t s
U.S. e m p l o y m e n t is classified by industry at t h e establish-
6
This information is b a s e d o n transactions data reported
S e e KPMG Peat Marwick (1989).
'Generally, t h e current surge in foreign investment m a y
reflect an a t t e m p t by foreign c o m p a n i e s to establish a
presence in U.S. industries. For example, eight Japanese
exporting has d r o p p e d while foreign investment has risen
manufacturers are increasing capacity t o b e a b l e to pro-
sharply in the 1977-86 p e r i o d m a y b e related to t h e strong
d u c e a r o u n d 2 million vehicles per year here. To the extent
value of the dollar in 1986 c o m p a r e d to 1977. Rather than
that foreign investment represents an a t t e m p t to erase a
export from the United States, foreign m u l t i n a t i o n a l cor-
g a p b e t w e e n actual a n d d e s i r e d stocks, future investment
p o r a t i o n s m a y h a v e s o u r c e d " e x p o r t s " in s o m e o t h e r
activity can b e expected to slow as t h e stock a d j u s t m e n t
country, including plants in their h o m e countries.
process matures.
S e e Kahley (1985, 1986, 1987).
References
Burnside, Yvonne. Key Company
New York: The
Directory.
Conference Board, August 1988.
Consulate General of Japan, lapanese
Subsidiaries
in the U.S. Southeast.
Firms,
Offices,
of Japanese
Firms
General
of lapan
the Consulate
Within
and
the Jurisdiction
in New
New
Orleans.
of U.S. Affiliates
Orleans, La., April I, 1989.
U.S. Direct
Abroad:
U.S.
Business.
Operations
and Their Foreign
Affiliates,
of
Pre-
Washington, D.C.: U.S. Govern-
1986 Estimates.
Survey of Current
Washington, D.C:
Business.
U.S. G o v e r n m e n t Printing Office, July 1988c.
" S t a t e Personal I n c o m e ,
of Current
Pre-
m e n t Printing Office, June 1988b.
May 28, 1989, section 3, 1, 8.
O p e r a t i o n s in 1986." Survey
Investment
U.S. Parent Companies
May 28, 1989, section 3, 9.
Howenstine, N e d G. "U.S. Affiliates of Foreign C o m p a n i e s :
States:
Companies,
m e n t Printing Office, June 1988a.
liminary
"The Takeover of American Industry." NewYork
in the United
of Foreign
Washington, D.C.: U.S. Govern-
1986 Estimates.
of
Hicks, Jonathan P. " Foreign Owners Are Shaking U p t h e Competition." New York Times,
Washington, D.C.: U.S.
1977-80.
Foreign Direct Investment
Operations
liminary
Consulate General of Japan in New Orleans. Offices
Times,
of U.S. Affiliates,
and
Atlanta, G a „ S e p t e m -
ber I, 1989.
Subsidiaries
tions
G o v e r n m e n t Printing Office, 1985.
E s t i m a t e s . " Survey
of Current
1985-87: Revised
Washington,
Business.
D.C.: U.S. G o v e r n m e n t Printing Office, August 1988d.
D e p a r t m e n t of C o m m e r c e . Bureau of E c o n o m i c Analysis.
"U.S. Direct I n v e s t m e n t A b r o a d : D e t a i l for
Washington, D.C.: U.S. G o v e r n m e n t Printing Office, May
Position a n d Balance of Payments Flows, 1 9 8 7 . " S u r v e y o f
1988.
Current
Kahley, William J. "Foreign Direct Investment - A Bonus for
t h e Southeast." Federal Reserve Bank of Atlanta
nomic
Review
Business.
Eco-
70 (June/July 1985): 4-17.
" U n i t e d S t a t e s D e p a r t m e n t of C o m m e r c e
News." News Release BEA 89-28. Washington, D.C.: U.S.
"What's B e h i n d Patterns of State Job G r o w t h ? "
Federal Reserve Bank of Atlanta Economic
Review
G o v e r n m e n t Printing Office, June 27, 1989a.
71
(May 1986): 4-18.
"Selected Data of Foreign Affiliates of U.S.
C o m p a n i e s . " C o m p u t e r printouts. July 1989b.
"Direct Investment Activity of Foreign Firms."
Federal Reserve Bank of Atlanta Economic
Review
72
(Summer 1987): 36-51.
KPMG Peat Marwick. Georgia
panies.
Com-
S e p t e m b e r 1989.
Business
Patterns.
"Selected Data of N o n b a n k U.S. Affiliates."
Photocopies. July 1989c.
U.S. D e p a r t m e n t of C o m m e r c e . International Trade Admini-
's 1989 Survey of Foreign
stration. International
and
U.S. D e p a r t m e n t of C o m m e r c e . B u r e a u of t h e C e n s u s .
County
Washington, D.C.: U.S. G o v e r n m e n t
Printing Office, August I988e.
1978, United
States.
the
1981.
Investment:
Global
Trends
Printing Office, August 1984.
CBP-78-1.
Washington, D.C.: U.S. Government Printing Office, April
Direct
U.S. Role. Washington, D.C.: U.S. G o v e r n m e n t
Foreign Direct Investment
1986 Transactions.
in the United
States:
Washington, D.C.: U.S. G o v e r n m e n t
Printing Office, S e p t e m b e r 1987.
County
Business
Patterns,
1986, United
States.
U.S. General Accounting Office. Foreign
Investment:
Grow-
CPB-86-1. Washington, D.C: U.S. G o v e r n m e n t Printing
ing lapanese
Office, O c t o b e r 1988.
ington, D C.: U.S. G o v e r n m e n t Printing Office, March
U.S. D e p a r t m e n t of Commerce. Bureau of Economic Analysis.
Foreign
Direct
Investment
in the United
FEDERAL RESERVE BANK OF ATLANTA
States:
Presence
in the U.S. Auto
Industry.
Wash-
1988.
Opera-
II
Book Review
Bank Costs, Structure,
and
Performance
by james Kolari and Asghar Zardkoohi.
Lexington, Mass.: D.C. Heath, 1987.
240 pages. $29.00.
C h a n g e s in b a n k i n g regulations in recent
years have created new opportunities for commercial banks and other financial institutions to
expand their operations. Restrictions on interstate b a n k i n g a n d intrastate branching have
b e e n liberalized in many states. In addition,
legislators and regulators have relaxed many
limitations formerly constraining t h e types of
services financial institutions could offer. Along
with these developments, though, have c o m e
new questions about t h e future structure of the
financial services industry. The industry's composition will d e p e n d to a great extent on the
types of financial institutions that can remain
profitable over time, a n d profitability will b e
determined largely by the extent to which banks
achieve production economies and resultant
cost reductions while expanding their operations.
Two types of production economies are generally available to banks—economies of scale
and economies of scope. Economies of scale
exist if average production costs decline as outp u t increases. Scope economies are present if
two or more products can b e jointly produced at
a lower cost than is incurred in their independ e n t production. In s o m e industries, such as
utilities, it is efficient for a single firm to supply
58
the entire industry output. These industries are
termed natural monopolies
and are characterized by economies of scale at every o u t p u t
level consumers are likely to d e m a n d . Recent
empirical evidence suggests that t h e cond itions
sufficient for natural monopoly in banking are
not satisfied over the relevant range of output.
Rather, overall economies of scale appear t o
exist only at low levels of output, and diseconomies, at large o u t p u t levels, suggesting a
U-shaped cost curve for t h e industry. 1
Against this b a c k d r o p , (ames Kolari a n d
Asghar Zardkoohi—professors of e c o n o m i c s
and public policy, respectively, at Texas A&M
University—undertake an important and timely
task. Bank Costs, Structure, and
Performance
provides a good introduction to the topic of cost
economics in banking and an in-depth review of
the pre-1985 literature on production economies. The authors reexamine t h e issue of scope
e c o n o m i e s in b a n k i n g a n d i n t r o d u c e a new
measure designed to estimate the extent of
these economies. In contrast to past research on
bank costs, Kolari a n d Zardkoohi perform separate analyses (using 1979-83 data) for banks with
differing market (product) characteristics. Unfortunately, t h e researchers fail to e m p h a s i z e
the qualified nature of the evidence they use to
ECONOMIC REVIEW, NOVEMBER/DECEMBER 1989
drawsome of their major conclusions and policy
implications. In particular, their cost complementarity and scope economy results should b e
interpreted with caution. Allen N. Berger addresses these and other shortcomings in another, earlier analysis of Kolari and Zardkoohi's work. 2
In the first chapter, Kolari and Zardkoohi set
the stage for their discussion of costs by describing the external and internal pressures on
banking that continue to affect bank profits:
increased competition from n o n b a n k institutions, the spread of interstate banking, product
line deregulation, and t h e rapid pace of technological advancement in the industry. These
developments have brought about a more competitive environment in which banks must operate as efficiently as p o s s i b l e . The authors'
historical overview of twentieth-century banking leads them to suggest that legal and regulatory c h a n g e s have greatly influenced t h e
structure of U.S. banking. Deregulation has already p u s h e d banks to b e c o m e more efficient,
but its lasting effects cannot b e foreseen without s o m e idea of how bank costs behave.
Kolari a n d Zardkoohi begin their study of
bank costs with a review of microeconomic production theory a n d how it may b e appl ied to the
special p r o b l e m s of banks. The authors also
delineate sources of scale and scope economies and describe how these are measured. In
their discussion of conceptual and methodological issues that arise in estimating such
economies, Kolari and Zardkoohi find that t h e
a p p r o p r i a t e d e f i n i t i o n of b a n k o u t p u t a n d
choice of functional form are especially important. Accurate measurement of b a n k o u t p u t is
necessary because economies of scale are defined in terms of t h e v o l u m e of t h e bank's
output.
The researchers analyze the choice of o u t p u t
measure a n d c o n c l u d e that dollar values of
loans and deposits, rather than n u m b e r of accounts, should b e used. Their argument is that
"banks c o m p e t e to increase market share of
dollar amounts as o p p o s e d to the n u m b e r of
accounts . . . |and| in a c o m p e t i t i v e b a n k i n g
environment the cost of an additional dollar of
both small and large accounts should b e t h e
same." Specification of the functional form of
the cost function (and therefore the underlying
production function) is also closely related to
FEDERAL RESERVE BANK OF ATLANTA
the measurement of scale and scope effects.
The production function identifies the relationship between the quantities of o u t p u t that result from the use of various quantities of inputs.
Comparing three economic production functions—
the Cobb-Douglas, constant elasticity of substitution, a n d translog f u n c t i o n s - t h e authors
assert that the last is the preferred form. It is
flexible enough to yield U-shaped cost curves
(diseconomies as well as economies of scale
and scope) and it allows for banks' characteristic
multiple inputs and outputs. 3
Chapter 3 presents a comprehensive survey
of previous literature on bank costs, divided
into three parts: (1) early studies that relied on
s i m p l e financial ratios to calculate bank costs,
(2) analyses from the mid-1960s and the 1970s
that used the Cobb-Douglas function and specified only o n e output, and (3) more recent works
that focus on the translog function. Notwithstanding the various studies' differences in
methodologies, output definitions, and data
sources, Kolari and Zardkoohi conclude from a
review of the earlier studies that "small banks
were at a cost disadvantage compared to large
b a n k s b u t that t h e difference was not so large
as to prevent them from competing effectively
" Recent research using the translog
cost model yielded results somewhat contrary
to those obtained earlier: very small banks were
found to b e cost-efficient for the most part. All of
the studies indicate that most scale economies
are exhausted when bank size reaches about
$25 million in deposits a n d that diseconomies
of scale exist at large o u t p u t levels, leading to
the familiar U-shaped cost function. However,
the evidence on scope economies was ambiguous. Even studies that found positive evidence
in favor of joint p r o d u c t i o n c o n c l u d e d that
scope benefits were not substantial enough to
alter the scale results.
In chapter 4 Kolari and Zardkoohi present the
econometric results of their own research. Using
Federal Reserve Functional Cost Analysis (FCA)
data for 1979-83, they e s t i m a t e three m o d e l s :
(1) d e m a n d deposits and time deposits, (2) loans
and securities, and (3) loans and deposits. 4 The
d e p e n d e n t variables are the allocated costs for
the specific outputs appearing in each regression model. The two researchers find average
cost curves to b e relatively flat in most cases, so
scale is apparently not an important cost deterII
minant. The major implication of a flat cost curve
is that many different sizes of banks should b e
a b l e to coexist. The authors perform jointness
tests a n d find that significant cost complementarities exist only in the joint production of loans
a n d deposits. Kolari a n d Zardkoohi also use
their new measure of scope economies, which
gauges t h e decrease in costs from producing
o u t p u t jointly, as compared to expanding total
o u t p u t by increasing each of t h e bank's products o n e at a t i m e (from the m i n i m u m level for
b a n k s of a b o u t t h e s a m e size). O n average,
Kolari and Zardkoohi find that banks can reduce
expansion costs a b o u t 30 percent to 50 percent
by increasing o u t p u t s at t h e s a m e time, as
o p p o s e d to increasing each output separately.
zero. A sufficient condition for cost complementarity requires that their cross-product term b e
not only negative b u t also greater in absolute
value than the product of their o u t p u t elasticities. 5 However, t h e cross-product terms reported by Kolari and Zardkoohi are positive in
most cases, suggesting that cost complementarity d o e s not hold or, if it does, that negative
e s t i m a t e d marginal costs are generating it.
Since the authors d o not provide the level of
complementarities or t h e estimated marginal
costs, it is impossible t o determine which condition exists. 6 The fact that Kolari a n d Zardkoohi
d o not investigate t h e scope economy results
for statistical significance further detracts from
their results.
Several issues a n d problems, both conceptual and methodological, may have influenced
the results reported in chapter 4. As a consequence, t h e usefulness of Kolari and Zardkoohi's conclusions in drawing policy implications,
although not eliminated, is limited. First, the
FCA data used in the analysis are heavily skewed
toward small banks. As of 1986, only 490 banks
participated in t h e program; o f t h i s n u m b e r , 4 1 6
held under $200 million in total deposits. To
draw conclusions a b o u t t h e cost structure of
large banks (over $1 billion in total deposits)
b a s e d on FCA data is not meaningful and can b e
misleading. Also, the FCA procedures for allocating costs are sometimes imprecise a n d may
induce bias in t h e results.
In chapter 5 t h e authors test t h e hypothesis
that differences in product mix influence b a n k
cost structures. Based on balance sheet ratios,
banks are clustered into four types: farm, retail,
city, and wholesale. Only farm banks were found
to have u n i q u e cost characteristics. (They exhibited flat cost curves where other groups had
U-shaped cost curves; they also h a d s c o p e
e c o n o m i e s related to d e p o s i t size.) All four
b a n k g r o u p s h a d higher scope economies in the
joint production of loans and deposits than in
t h e other two models. Kolari and Zardkoohi's
results are puzzling, nonetheless. Several researchers who h a n d l e d differing product mixes
by specifying more outputs in the cost function
have rejected t h e h y p o t h e s i s that different
asset a n d liability categories can b e aggregated. 7 Ideally, each bank product should b e
included as a distinct output, b u t the availabil ity of data and use of the translog functional
form usually limit t h e level of disaggregation. 8
A second p r o b l e m that may distort t h e results
is that Kolari and Zardkoohi exclude interest
payments from their cost measure. Berger, Gerald A. Hanweck, and David B. Humphrey (1987)
have shown that studies using dollar measures
of o u t p u t s a n d total o p e r a t i n g costs as t h e
d e p e n d e n t variable are biased toward finding
scale e c o n o m i e s b e c a u s e b a n k s can fund a
larger asset portfolio by increasing purchased
funds. Thus, Kolari and Zardkoohi's analysis is
biased by a bank's choice to gather deposits
through a branching network or to purchase
funds from other retail banks.
A third problem arises with interpreting the
authors' cost complementarity and scope economy results. When t h e results from the translog
cost function are used, a necessary condition for
the existence of cost complementarity between
two products is that their cross-product term
(8, 2 ) b e negative and statistically different from
60
Kolari a n d Zardkoohi turn from static costs to
the impact of technological improvements in
banking a n d how they have affected production
costs. To test whether larger scale allows more
cost-efficient use of technology, t h e authors
regress d e m a n d d e p o s i t costs on the ratio of
computer-related costs to labor costs and s o m e
o u t p u t variables. The closer this ratio is to zero,
t h e greater the cost savings by substituting computer technology for labor. Kolari a n d Zardkoohi
in fact find that t h e coefficient lies between zero
and one, suggesting that cost savings result.
They find n o evidence of a trend toward greater
cost gains by large banks. However, whether this
model is sufficiently c o m p l e t e to draw such a
ECONOMIC REVIEW, NOVEMBER/DECEMBER 1989
conclusion is unclear. In particular, the authors
have a very narrow view of technological change
and t h e a p p r o p r i a t e costs that are affected.
They ignore the possibility that technological
innovation can take the form of new production
processes rather than equipment. Another problem with Kolari and Zardkoohi's model is that
only d e m a n d d e p o s i t costs are included in t h e
d e p e n d e n t variable. 9
Finally, t h e authors examine the relation between cost efficiency a n d b a n k failure using Call
Report data for 1984. They develop an earlywarning-system model based on commonly used
financial ratios and individual b a n k cost measures (scale economies and residual costs) generated in the research reported earlier in t h e
book. The cost measures were found t o improve
the predictive power of the failure model substantially when a d d e d to financial ratios. Problems exist with the analysis, though, because
Kolari a n d Zardkoohi fall into t h e trap that
earlier writers did. By regressing identical operating expenses on loans a n d deposits separately, t h e authors' analysis suffers from t h e
same drawbacks as t h e study by Thomas W.
Gilligan a n d Michael Smirlock (1984): i n p u t
prices are assumed to b e constant a n d other
bank services are excluded even though they
affect total operating expenses. This practice
gives a bias toward finding both scale and scope
FEDERAL RESERVE BANK OF ATLANTA
economies a n d leads t h e m to conclude that failing banks were smaller than average.
From a policy perspective, the evidence presented in the b o o k appears to minimize any
concern that the banking industry will b e dominated by a few large institutions. The lifting of
restrictions on interstate banking and intrastate
branching might help consolidate resources in
states that have limited branch banking and
thereby permit small banks to achieve a more
efficient scale of production.
O n t h e whole, Bank Costs, Structure, and Performance is a useful g u i d e to future work in this
area and is of interest to academicians, policymakers, a n d practitioners. It provides an ind e p t h look at the literature, introduces a new
measure of scope economies, and o p e n s s o m e
new lines of research. The book's biggest failing
is the absence of necessary qualifications in
regard to the econometric evidence it presents
and the consequent potential to mislead readers.
Aruna Srinivasan
The reviewer
Atlanta
is an economist
Fed's Research
in the financial
section
of the
Department.
II
Notes
offered by t h e bank, a n d costs i n c l u d e b o t h interest a n d
'See, for e x a m p l e , Hunter a n d T i m m e (1989) a n d Lawrence
a n d Shay (1986).
o p e r a t i n g expenses. The i n t e r m e d i a t i o n a p p r o a c h uses a
2
S e e Berger (1988).
broader definition of costs a n d is c o n s i d e r e d t o b e m o r e
3
T h e m a i n d i s a d v a n t a g e of t h e Cobb-Douglas production
relevant for a d d r e s s i n g i s s u e s relating t o t h e long-run
function is that it only allows for uniform scale characteris-
viability of b a n k s (Hunter a n d T i m m e 119891).
4
tics, while t h e constant elasticity of substitution function is
5
S e e Clark (1988).
highly restrictive in cases where firms p r o d u c e m o r e than
6
O t h e r s t u d i e s (Benston et al. 119831, Mester |I987|) ex-
o n e o u t p u t or u s e m o r e than o n e factor input.
plicitly report negative marginal costs for s o m e products,
A l t h o u g h FCA data p r o v i d e information o n t h e n u m b e r of
attributing t h e m t o e s t i m a t i o n p r o b l e m s such as the pres-
accounts, Kolari a n d Zardkoohi prefer t o use dollar a m o u n t s
e n c e of multicollinearity a n d loss of degrees of freedom.
for t h e reasons m e n t i o n e d earlier. In general, researchers
7
S e e Kim (1986) a n d Lawrence a n d Shay (1986).
take o n e of two a p p r o a c h e s in defining b a n k costs a n d out-
8
S e e Clark (1988).
p u t : the p r o d u c t i o n a p p r o a c h or the i n t e r m e d i a t i o n ap-
9
I t is also i m p o r t a n t to n o t e that Kolari a n d Zardkoohi's con-
proach (Berger, Hanweck, a n d H u m p h r e y |I987|). U n d e r
clusions are l i m i t e d to t h e smaller b a n k s in t h e economy.
t h e p r o d u c t i o n approach, o u t p u t is m e a s u r e d in terms of
H u n t e r a n d T i m m e (1986, 1988) e x a m i n e the relation be-
t h e n u m b e r of loan a n d d e p o s i t accounts, a n d costs are
tween technological change, p r o d u c t i o n e c o n o m i e s , a n d
d e f i n e d a s total operating e x p e n s e s exclusive of interest
firm size for a s a m p l e of large b a n k s a n d find that larger
costs. The i n t e r m e d i a t i o n approach, o n t h e other h a n d ,
b a n k s e n j o y p r o p o r t i o n a t e l y h i g h e r cost savings from
m e a s u r e s o u t p u t as t h e d o l l a r v a l u e of t h e p r o d u c t s
technological change.
References
Benston, G e o r g e )., Allen N. Berger, Gerald A. Hanweck, a n d
David B. H u m p h r e y . " E c o n o m i c s of Scale a n d S c o p e . " In
of Money,
Credit,
and Banking
Com-
Hunter, William C., a n d S t e p h e n G. T i m m e . "Technological
C h a n g e in Large U.S. Commercial Banks." Federal Re-
of a Conference
on Bank Structure
and
serve Bank of Atlanta Working Paper 88-6 ( D e c e m b e r
432-55.
Berger, Allen N. In "Book Reviews." tournai
and Banking
of Money,
Credit,
20 (May 1988): 283-87.
1988).
Hunter, William C , a n d S t e p h e n G. T i m m e . " D o e s Multi-
Berger, Allen N., Gerald A. Hanweck, a n d David B. Hum-
p r o d u c t P r o d u c t i o n in Large Banks R e d u c e C o s t s ? "
phrey. " C o m p e t i t i v e Viability in Banking: Scale, Scope,
Federal Reserve Bank of Atlanta Economic
a n d Product Mix Economies." Journal
(May/June 1989): 2-11.
nomics
18 (May
1986): 152-66.
Federal Reserve Bank of Chicago (May 1983):
Proceedings
petition.
d u c t i o n . " /ournal
of Monetary
Eco-
20 ( D e c e m b e r 1987): 501-20.
pository Financial Institutions." Federal Reserve Bank of
Review
74
Kim, Moshe. "Banking Technology a n d t h e Existence of a
Clark, leffrey A. " E c o n o m i e s of Scale a n d S c o p e at DeK a n s a s City Economic
Review
(September/October
1988): 16-33.
C o n s i s t e n t O u t p u t A g g r e g a t e . " / o u r n a l of
Economics
Monetary
18 ( S e p t e m b e r 1986): 181-95.
Lawrence, Colin, a n d Robert Shay. "Technology a n d Financial I n t e r m e d i a t i o n in M u l t i p r o d u c t Banking Firms: An
Gilligan, T h o m a s W., a n d Michael Smirlock. "An Empirical
Econometric Study of U.S. Banks, 1979-1982." In
Tech-
Study of Joint Production a n d Scale E c o n o m i e s in Com-
nological
mercial B a n k i n g . " tournai
8
my, e d i t e d by Lawrence a n d Shay. C a m b r i d g e , Mass.:
Hunter, W i l l i a m C , a n d S t e p h e n G. T i m m e . "Technical
Mester, Loretta). "A M u l t i p r o d u c t Cost Study of Savings a n d
of Banking
and
Finance
(March 1984): 67-77.
Change, Organizational Form, a n d Structure of Bank Pro-
62
Innovation,
Regulation
and the Monetary
Econo-
Ballenger, 1986.
Loans." / o u r n a l of Finance
42 (June 1987): 423-45.
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An Examination
89-4
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Preston J. Miller a n d William R o b e r d s
How Little
89-5
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Analytic
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89-6
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Economic
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BOOK REVIEWS
Bank Costs, Structure, and Performance by lames
Kolari and Asghar Zardkoohi (Lexington, Mass.:
D.C. Heath, 1987)
Aruna Srinivasan, November/December, 58
Breaking the Bank: The Decline of BankAmerica
by Gary Hector (Boston: Little, Brown, 1988)
B. Frank King and Sheila L. Tschinkel,
September/October, 48
Breaking Up the Bank: Rethinking an Industry
under Seige by Lowell L. Bryan (Homewood, III.:
Dow Jones-Irwin, 1988)
B. Frank King and Sheila L. Tschinkel,
September/October, 48
The Cold Standard and the International
Monetary
System 1900-1939 by Ian M. Drummond (London:
MacMillan Education Ltd., 1987)
Thomas J. Cunningham, March/April, 50
Migration and Residential Mobility in the United
States by Larry Long (New York: Russell Sage
Foundation, 1988)
William J. Kahley, May/June, 52
Memoirs of an Unregulated Economist by George J.
Stigler (New York: Basic Books, 1988)
Mary Susan Rosenbaum, July/August, 48
The Netherlands and the Gold Standard, 19311936: A Study in Policy Formation and Policy
edited by Richard T. Griffiths (Amsterdam:
Nederlandsch Economisch-Historisch Archief, 1987)
Thomas J. Cunningham, March/April, 50
CORPORATE FINANCE
"Bank Merger Motivations: A Review of the
Evidence and an Examination of Key Target Bank
Characteristics"
William C. Hunter and Larry D. Wall,
September/October, 2
"Capital Requirements for Banks: A Look at the
1981 and 1988 Standards"
Larry D. Wall, March/April, 14
64
"Financial Asset Pricing Theory: A Review of
Recent Developments"
Ellis W. Tallman, November/December, 26
"Forecasting Stock-Market Volatility Using Options
on Index Futures"
Steven P. Feinstein, May/June, 12
"Interest-Rate Caps, Collars, and Floors"
Peter A. Abken, November/December, 2
"A Plan for Reducing Future Deposit Insurance
Losses: Puttable Subordinated Debt"
Larry D. Wall, |uly/August, 2
FEDERAL DEFICIT
"The Federal Budget Deficit and the Social
Security Surplus"
Thomas J. Cunningham, March/April, 2
FINANCIAL INSTITUTIONS
"Bank Merger Motivations: A Review of the
Evidence and an Examination of Key Target Bank
Characteristics"
William C. Hunter and Larry D. Wall,
September/October, 2
Book Review: Bank Costs, Structure, and Performance by lames Kolari and Asghar Zardkoohi
Aruna Srinivasan, November/December, 58
Book Review: Breaking the Bank: The Decline
BankAmerica by Gary Hector
B. Frank King and Sheila L. Tschinkel,
September/October, 48
of
Book Review: Breaking Up the Bank: Rethinking
Industry under Seige by Lowell L. Bryan
B. Frank King and Sheila L. Tschinkel,
September/October, 48
an
"Capital Requirements for Banks: A Look at the
1981 and 1988 Standards"
Larry D. Wall, March/April, 14
"Commercial Bank Profitability: Improved in 1988"
Robert E. Goudreau and David D. Whitehead,
)uly/August, 34
ECONOMIC REVIEW, NOVEMBER/DECEMBER 1989
Index for 1989
"Does Multiproduct Production in Large Banks
Reduce Costs?"
William Curt Hunter and Stephen G. Timme,
May/June, 2
"Interstate Banking Developments in the 1980s"
B. Frank King, Sheila L. Tschinkel, and David D.
Whitehead, May/June, 32
INTERSTATE BANKING
"Interstate Banking Developments in the 1980s"
B. Frank King, Sheila L. Tschinkel, and David D.
Whitehead, May/June, 32
MACROECONOMIC POLICY
"A Plan for Reducing Future Deposit Insurance
Losses: Puttable Subordinated Debt"
Larry D. Wall, July/August, 2
Book Review: The Gold Standard and the International Monetary System 1900-1939 by
Ian M. Drummond
Thomas J. Cunningham, March/April, 50
FOREIGN INVESTMENT IN THE
UNITED STATES
Book Review: The Netherlands and the Gold Standard, 1931-1936: A Study in Policy Formation and
Policy edited by Richard T. Griffiths
Thomas J. Cunningham, March/April, 50
"U.S. and Foreign Direct Investment Patterns"
William J. Kahley, November/December, 42
GOLD STANDARD
Book Review: The Gold Standard and the
national Monetary System 1900-1939 by
Ian M. Drummond
Inter-
"The Federal Budget Deficit and the Social
Security Surplus"
Thomas J. Cunningham, March/April, 2
"Money and the Economy: Puzzles from the 1980s'
Experience"
William Roberds, September/October, 20
Thomas J. Cunningham, March/April, 50
Book Review: The Netherlands and the Gold Standard, 1931-1936: A Study in Policy Formation and
Policy edited by Richard T. Griffiths
Thomas j. Cunningham, March/April, 50
INTERNATIONAL ECONOMICS
Book Review: The Cold Standard and the International Monetary System 1900-1939 by
Ian M. Drummond
Thomas J. Cunningham, March/April, 50
"Purchasing-Power Parity and Exchange Rates in
the Long Run"
Joseph A. Whitt, Jr., July/August, 18
"U.S. and Foreign Direct Investment Patterns"
William J. Kahley, November/December, 42
MANUFACTURING
"Southeastern Manufacturing: Recent Changes and
Prospects"
Gene D. Sullivan and David Avery, january/
February, 2
MIGRATION
Book Review: Migration and Residential
in the United States by Larry Long
William J. Kahley, May/June, 52
Mobility
"Interregional Migration: Boon or Bane for the
South"
William J. Kahley, January/February, 18
MONEY SUPPLY
"Money and the Economy: Puzzles from the 1980s'
Experience"
William Roberds, September/October, 20
II
FEDERAL RESERVE BANK OF ATLANTA
POVERTY
"Poverty in the South"
jon R. Moen, January/February, 36
PUBLIC FINANCE
"Measuring State and Local Fiscal Capacities in
the Southeast"
Aruna Srinivasan, September/October, 36
"Public Finance and Economic Growth in the
Southeast"
Aruna Srinivasan, January/February, 48
REGIONAL ECONOMICS
"Interregional Migration: Boon or Bane for the
South"
William J. Kahley, lanuary/February, 18
"Measuring State and Local Fiscal Capacities in
the Southeast"
Aruna Srinivasan, September/October, 36
"Poverty in the South"
Jon R. Moen, January/February, 36
"Public Finance and Economic Growth in the
Southeast"
Aruna Srinivasan, January/February, 48
"Southeastern Manufacturing: Recent Changes and
Prospects"
Gene D. Sullivan and David Avery, January/
February, 2
"U.S. and Foreign Direct Investment Patterns"
William J. Kahley, November/December, 42
SECURITIES
"Financial Asset Pricing Theory: A Review of
Recent Developments"
Ellis W. Tall man, November/December, 26
66
"Forecasting Stock-Market Volatility Using Options
on Index Futures"
Steven P. Feinstein, May/June, 12
"Interest-Rate Caps, Collars, and Floors"
Peter A. Abken, November/December, 2
SOCIAL SECURITY
"The Federal Budget Deficit and the Social
Security Surplus"
Thomas J. Cunningham, March/April, 2
STOCK MARKET
"Financial Asset Pricing Theory: A Review of
Recent Developments"
Ellis W. Tallman, November/December, 26
"Forecasting Stock-Market Volatility Using Options
on Index Futures"
Steven P. Feinstein, May/June, 12
U.S. ECONOMY
Book Review: Migration and Residential
in the United States by Larry Long
William J. Kahley, May/June, 52
Mobility
"The Federal Budget Deficit and the Social
Security Surplus"
Thomas J. Cunningham, March/April, 2
"Money and the Economy: Puzzles from the 1980s'
Experience"
William Roberds, September/October, 20
"Tracking the Economy: Fundamentals for
Understanding Data"
R. Mark Rogers: March/April, 30
"U.S. and Foreign Direct Investment Patterns"
William J. Kahley, November/December, 42
ECONOMIC REVIEW, NOVEMBER/DECEMBER 1989
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Atlanta Fed History Now Available
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